Expansión de la CASEN sobre el CENSO (Región 12)

De ingresos sobre una categoría de respuesta

DataIntelligence

Abstract

Expandiremos los ingresos promedios comunales obtenidos de la CASEN sobre la categoría de respuesta: “tejas o tejuelas de arcilla, metálicas, de cemento, de madera, asfálticas o plásticas” del campo P03B del CENSO de viviendas, que fue la categoría de respuesta que más alto correlaciona con los ingresos expandidos (obtenidos de la multiplicación del ingreso promedio y los habitantes), ambos a nivel comunal.

Haremos el análisis sobre la región 12.

Ensayaremos diferentes modelos dentro del análisis de regresión cuya variable independiente será: “frecuencia de población que posee la variable Censal respecto a la zona” y la dependiente: “ingreso expandido por zona”

Lo anterior para elegir el que posea el mayor coeficiente de determinación y así contruir una tabla de valores predichos.

1 Variable CENSO

Necesitamos calcular las frecuencias a nivel censal de las respuestas correspondientes a la categoría: “tejas o tejuelas de arcilla, metálicas, de cemento, de madera, asfálticas o plásticas” del campo P03B del Censo de viviendas. Recordemos que ésta fué la más alta correlación en relación a los ingresos expandidos (ver punto 1.2 aquí).

1.1 Lectura y filtrado de la tabla censal de viviendas

Leemos la tabla Casen 2017 de viviendas que ya tiene integrada la clave zonal:

tabla_con_clave <- readRDS("censo_viviendas_con_clave_17.rds")
r3_100 <- tabla_con_clave[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

REGION	PROVINCIA	COMUNA	DC	AREA	ZC_LOC	ID_ZONA_LOC	NVIV	P01	P02	P03A	P03B	P03C	P04	P05	CANT_HOG	CANT_PER	REGION_15R	PROVINCIA_15R	COMUNA_15R	clave
15	152	15202	1	2	6	13225	1	3	1	5	3	5	1	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	2	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	3	1	1	5	3	5	2	3	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	4	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	5	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	6	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	7	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	8	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	9	3	1	5	3	5	1	4	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	10	1	1	5	3	4	1	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	11	1	2	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	12	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	13	1	1	5	3	4	1	4	1	3	15	152	15202	15202012006
15	152	15202	1	2	6	13225	14	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	15	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	16	1	1	5	3	5	1	3	1	3	15	152	15202	15202012006
15	152	15202	1	2	6	13225	17	1	1	5	3	5	2	4	1	8	15	152	15202	15202012006
15	152	15202	1	2	6	13225	18	3	1	5	3	5	1	1	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	19	3	1	5	3	5	1	3	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	20	1	1	5	3	5	2	1	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	21	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	22	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	23	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	24	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	25	1	1	5	3	5	1	4	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	26	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	27	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	28	3	1	5	3	5	1	4	1	5	15	152	15202	15202012006
15	152	15202	1	2	6	13225	29	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	30	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	31	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	32	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	33	1	1	5	3	5	3	4	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	34	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	35	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	36	1	1	5	3	5	3	2	1	9	15	152	15202	15202012006
15	152	15202	1	2	6	13225	37	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	38	1	1	5	3	5	99	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	39	1	1	5	3	5	1	4	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	40	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	41	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	42	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	43	3	1	5	3	5	2	1	1	5	15	152	15202	15202012006
15	152	15202	1	2	6	13225	44	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	45	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	8	13910	1	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	2	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	3	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	4	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	5	3	1	5	3	5	2	3	1	3	15	152	15202	15202012008
15	152	15202	1	2	8	13910	6	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	7	1	1	5	99	5	2	4	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	8	3	1	5	3	5	3	3	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	9	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	10	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	11	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	12	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	13	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	14	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	15	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	16	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	17	3	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	18	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	19	3	1	99	99	99	99	99	1	1	15	152	15202	15202012008
15	152	15202	1	2	8	13910	20	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	21	1	1	5	3	5	1	4	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	22	3	1	5	3	5	2	4	1	1	15	152	15202	15202012008
15	152	15202	1	2	8	13910	23	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	24	3	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	25	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	26	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	27	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	28	3	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	29	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	30	1	1	5	1	4	2	4	1	1	15	152	15202	15202012008
15	152	15202	1	2	12	8394	1	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	2	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	3	3	1	5	3	5	2	3	1	4	15	152	15202	15202012012
15	152	15202	1	2	12	8394	4	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	5	3	3	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	6	3	3	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	7	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	8	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	9	3	1	5	3	5	1	4	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	10	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	11	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	12	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	13	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	14	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	15	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	16	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	17	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	18	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	19	3	1	99	99	99	99	99	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	20	3	1	5	3	5	3	99	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	21	3	1	5	99	5	1	4	1	2	15	152	15202	15202012012
15	152	15202	1	2	12	8394	22	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	23	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	24	3	1	5	3	5	1	2	1	2	15	152	15202	15202012012
15	152	15202	1	2	12	8394	25	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012

Despleguemos los códigos de regiones de nuestra tabla:

regiones <- unique(tabla_con_clave$REGION)
regiones

##  [1] 15 14 13 12 11 10  9 16  8  7  6  5  4  3  2  1

Hagamos un subset con la 1:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 12) 

1.2 Cálculo de frecuencias

tabla_con_clave_f <- tabla_con_clave[,-c(1,2,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20),drop=FALSE] 
names(tabla_con_clave_f)[2] <- "Tipo de techo" 
# Ahora filtramos por Tipo de techo = 1.
tabla_con_clave_ff <- filter(tabla_con_clave_f, tabla_con_clave_f$`Tipo de techo` == 1)
# Determinamos las frecuencias por zona:
b <- tabla_con_clave_ff$clave
c <- tabla_con_clave_ff$`Tipo de techo`
d <- tabla_con_clave_ff$COMUNA
cross_tab =  xtabs( ~ unlist(b) + unlist(c)+ unlist(d))
tabla <- as.data.frame(cross_tab)
d <-tabla[!(tabla$Freq == 0),]
names(d)[1] <- "zona" 
d$anio <- "2017"

Veamos los primeros 100 registros:

r3_100 <- d[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	zona	unlist.c.	unlist.d.	Freq	anio
1	12101011001	1	12101	108	2017
2	12101011002	1	12101	563	2017
3	12101011003	1	12101	125	2017
4	12101011004	1	12101	162	2017
5	12101021001	1	12101	137	2017
6	12101021002	1	12101	148	2017
7	12101031001	1	12101	303	2017
8	12101031002	1	12101	171	2017
9	12101031003	1	12101	98	2017
10	12101031004	1	12101	161	2017
11	12101031005	1	12101	180	2017
12	12101041001	1	12101	163	2017
13	12101041002	1	12101	151	2017
14	12101041003	1	12101	104	2017
15	12101041004	1	12101	159	2017
16	12101041005	1	12101	82	2017
17	12101041006	1	12101	75	2017
18	12101041007	1	12101	86	2017
19	12101051001	1	12101	85	2017
20	12101051002	1	12101	30	2017
21	12101061001	1	12101	75	2017
22	12101061002	1	12101	92	2017
23	12101061003	1	12101	63	2017
24	12101071001	1	12101	56	2017
25	12101071002	1	12101	193	2017
26	12101071003	1	12101	113	2017
27	12101071004	1	12101	96	2017
28	12101071005	1	12101	120	2017
29	12101071006	1	12101	411	2017
30	12101071007	1	12101	213	2017
31	12101081001	1	12101	83	2017
32	12101081002	1	12101	83	2017
33	12101081003	1	12101	62	2017
34	12101081004	1	12101	157	2017
35	12101081005	1	12101	97	2017
36	12101081006	1	12101	137	2017
37	12101091001	1	12101	19	2017
38	12101092005	1	12101	66	2017
39	12101092006	1	12101	2	2017
40	12101092009	1	12101	4	2017
41	12101092016	1	12101	7	2017
42	12101092019	1	12101	24	2017
43	12101092020	1	12101	41	2017
44	12101092032	1	12101	54	2017
45	12101092901	1	12101	1	2017
46	12101101001	1	12101	2	2017
47	12101101002	1	12101	73	2017
48	12101101003	1	12101	169	2017
49	12101101004	1	12101	149	2017
50	12101101005	1	12101	85	2017
51	12101102002	1	12101	1	2017
52	12101102015	1	12101	23	2017
53	12101102021	1	12101	24	2017
54	12101102029	1	12101	6	2017
55	12101102030	1	12101	7	2017
56	12101102033	1	12101	1	2017
57	12101102901	1	12101	1	2017
58	12101122001	1	12101	4	2017
59	12101142011	1	12101	3	2017
60	12101991999	1	12101	3	2017
167	12102012012	1	12102	1	2017
168	12102012014	1	12102	3	2017
169	12102012015	1	12102	1	2017
170	12102012017	1	12102	4	2017
171	12102012020	1	12102	2	2017
172	12102012901	1	12102	5	2017
279	12103012014	1	12103	1	2017
280	12103012019	1	12103	1	2017
281	12103022009	1	12103	1	2017
388	12104012008	1	12104	1	2017
389	12104012010	1	12104	2	2017
390	12104022901	1	12104	1	2017
497	12201011001	1	12201	140	2017
498	12201012901	1	12201	2	2017
605	12301011001	1	12301	61	2017
606	12301011002	1	12301	87	2017
607	12301012005	1	12301	2	2017
608	12301012007	1	12301	5	2017
609	12301012008	1	12301	3	2017
610	12301022001	1	12301	1	2017
611	12301032003	1	12301	1	2017
612	12301032011	1	12301	1	2017
719	12302012005	1	12302	15	2017
720	12302012901	1	12302	1	2017
827	12303012005	1	12303	1	2017
828	12303012009	1	12303	1	2017
829	12303012010	1	12303	1	2017
830	12303012012	1	12303	1	2017
831	12303012901	1	12303	3	2017
938	12401011001	1	12401	68	2017
939	12401011002	1	12401	154	2017
940	12401011003	1	12401	63	2017
941	12401011004	1	12401	103	2017
942	12401011005	1	12401	65	2017
943	12401011006	1	12401	89	2017
944	12401011007	1	12401	80	2017
945	12401011008	1	12401	196	2017
946	12401012010	1	12401	3	2017
947	12401012017	1	12401	1	2017
948	12401012022	1	12401	1	2017

Agregamos un cero a los códigos comunales de cuatro dígitos:

codigos <- d$unlist.d.
rango <- seq(1:nrow(d))
cadena <- paste("0",codigos[rango], sep = "")
cadena <- substr(cadena,(nchar(cadena)[rango])-(4),6)
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
comuna_corr <- cbind(d,cadena)
comuna_corr <- comuna_corr[,-c(2,3),drop=FALSE]
names(comuna_corr)[4] <- "código" 
r3_100 <- comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	zona	Freq	anio	código
1	12101011001	108	2017	12101
2	12101011002	563	2017	12101
3	12101011003	125	2017	12101
4	12101011004	162	2017	12101
5	12101021001	137	2017	12101
6	12101021002	148	2017	12101
7	12101031001	303	2017	12101
8	12101031002	171	2017	12101
9	12101031003	98	2017	12101
10	12101031004	161	2017	12101
11	12101031005	180	2017	12101
12	12101041001	163	2017	12101
13	12101041002	151	2017	12101
14	12101041003	104	2017	12101
15	12101041004	159	2017	12101
16	12101041005	82	2017	12101
17	12101041006	75	2017	12101
18	12101041007	86	2017	12101
19	12101051001	85	2017	12101
20	12101051002	30	2017	12101
21	12101061001	75	2017	12101
22	12101061002	92	2017	12101
23	12101061003	63	2017	12101
24	12101071001	56	2017	12101
25	12101071002	193	2017	12101
26	12101071003	113	2017	12101
27	12101071004	96	2017	12101
28	12101071005	120	2017	12101
29	12101071006	411	2017	12101
30	12101071007	213	2017	12101
31	12101081001	83	2017	12101
32	12101081002	83	2017	12101
33	12101081003	62	2017	12101
34	12101081004	157	2017	12101
35	12101081005	97	2017	12101
36	12101081006	137	2017	12101
37	12101091001	19	2017	12101
38	12101092005	66	2017	12101
39	12101092006	2	2017	12101
40	12101092009	4	2017	12101
41	12101092016	7	2017	12101
42	12101092019	24	2017	12101
43	12101092020	41	2017	12101
44	12101092032	54	2017	12101
45	12101092901	1	2017	12101
46	12101101001	2	2017	12101
47	12101101002	73	2017	12101
48	12101101003	169	2017	12101
49	12101101004	149	2017	12101
50	12101101005	85	2017	12101
51	12101102002	1	2017	12101
52	12101102015	23	2017	12101
53	12101102021	24	2017	12101
54	12101102029	6	2017	12101
55	12101102030	7	2017	12101
56	12101102033	1	2017	12101
57	12101102901	1	2017	12101
58	12101122001	4	2017	12101
59	12101142011	3	2017	12101
60	12101991999	3	2017	12101
167	12102012012	1	2017	12102
168	12102012014	3	2017	12102
169	12102012015	1	2017	12102
170	12102012017	4	2017	12102
171	12102012020	2	2017	12102
172	12102012901	5	2017	12102
279	12103012014	1	2017	12103
280	12103012019	1	2017	12103
281	12103022009	1	2017	12103
388	12104012008	1	2017	12104
389	12104012010	2	2017	12104
390	12104022901	1	2017	12104
497	12201011001	140	2017	12201
498	12201012901	2	2017	12201
605	12301011001	61	2017	12301
606	12301011002	87	2017	12301
607	12301012005	2	2017	12301
608	12301012007	5	2017	12301
609	12301012008	3	2017	12301
610	12301022001	1	2017	12301
611	12301032003	1	2017	12301
612	12301032011	1	2017	12301
719	12302012005	15	2017	12302
720	12302012901	1	2017	12302
827	12303012005	1	2017	12303
828	12303012009	1	2017	12303
829	12303012010	1	2017	12303
830	12303012012	1	2017	12303
831	12303012901	3	2017	12303
938	12401011001	68	2017	12401
939	12401011002	154	2017	12401
940	12401011003	63	2017	12401
941	12401011004	103	2017	12401
942	12401011005	65	2017	12401
943	12401011006	89	2017	12401
944	12401011007	80	2017	12401
945	12401011008	196	2017	12401
946	12401012010	3	2017	12401
947	12401012017	1	2017	12401
948	12401012022	1	2017	12401

2 Variable CASEN

2.1 Tabla de ingresos expandidos

Hemos calculado ya éste valor como conclusión del punto 1.1 de aquí

h_y_m_2017_censo <- readRDS("ingresos_expandidos_17.rds")
tablamadre <- head(h_y_m_2017_censo,50)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
01101	Iquique	354820.7	2017	1101	191468	67936815240
01107	Alto Hospicio	301933.4	2017	1107	108375	32722034397
01401	Pozo Almonte	285981.8	2017	1401	15711	4493059532
01402	Camiña	262850.3	2017	1402	1250	328562901
01404	Huara	253968.5	2017	1404	2730	693334131
01405	Pica	313007.5	2017	1405	9296	2909717399
02101	Antofagasta	347580.2	2017	2101	361873	125779893517
02102	Mejillones	369770.7	2017	2102	13467	4979702302
02103	Sierra Gorda	403458.5	2017	2103	10186	4109628188
02104	Taltal	364539.1	2017	2104	13317	4854566842
02201	Calama	409671.3	2017	2201	165731	67895226712
02203	San Pedro de Atacama	426592.0	2017	2203	10996	4690805471
02301	Tocopilla	246615.3	2017	2301	25186	6211253937
02302	María Elena	466266.9	2017	2302	6457	3010685220
03101	Copiapó	330075.2	2017	3101	153937	50810778473
03102	Caldera	299314.8	2017	3102	17662	5286498241
03103	Tierra Amarilla	314643.9	2017	3103	14019	4410992711
03201	Chañaral	286389.3	2017	3201	12219	3499391196
03202	Diego de Almagro	336256.8	2017	3202	13925	4682376047
03301	Vallenar	304336.7	2017	3301	51917	15800246795
03302	Alto del Carmen	227130.4	2017	3302	5299	1203563833
03303	Freirina	253086.7	2017	3303	7041	1781983257
03304	Huasco	287406.6	2017	3304	10149	2916889629
04101	La Serena	270221.9	2017	4101	221054	59733627577
04102	Coquimbo	261852.6	2017	4102	227730	59631700074
04103	Andacollo	248209.3	2017	4103	11044	2741223967
04104	La Higuera	228356.8	2017	4104	4241	968461330
04105	Paiguano	205942.1	2017	4105	4497	926121774
04106	Vicuña	211431.9	2017	4106	27771	5871675449
04201	Illapel	238674.4	2017	4201	30848	7362627007
04202	Canela	207933.6	2017	4202	9093	1890740321
04203	Los Vilos	255200.4	2017	4203	21382	5456695139
04204	Salamanca	242879.5	2017	4204	29347	7127783272
04301	Ovalle	266522.9	2017	4301	111272	29656533187
04302	Combarbalá	210409.7	2017	4302	13322	2803077721
04303	Monte Patria	211907.9	2017	4303	30751	6516380780
04304	Punitaqui	194997.8	2017	4304	10956	2136395349
04305	Río Hurtado	182027.2	2017	4305	4278	778712384
05101	Valparaíso	298720.7	2017	5101	296655	88616992249
05102	Casablanca	312802.7	2017	5102	26867	8404070481
05103	Concón	318496.3	2017	5103	42152	13425257057
05105	Puchuncaví	288737.2	2017	5105	18546	5354920887
05107	Quintero	316659.1	2017	5107	31923	10108709691
05109	Viña del Mar	337006.1	2017	5109	334248	112643604611
05301	Los Andes	338182.5	2017	5301	66708	22559476922
05302	Calle Larga	245165.4	2017	5302	14832	3636293159
05303	Rinconada	281633.2	2017	5303	10207	2874630315
05304	San Esteban	220958.4	2017	5304	18855	4166170587
05401	La Ligua	229623.7	2017	5401	35390	8126381563
05402	Cabildo	249717.7	2017	5402	19388	4841527150

3 Unión Censo-Casen

Integramos a la tabla censal de frecuencias la tabla de ingresos expandidos de la Casen.

comunas_con_ing_exp = merge( x = comuna_corr, y = h_y_m_2017_censo, by = "código", all.x = TRUE)
r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	zona	Freq	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
12101	12101011004	162	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101011001	108	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101011003	125	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041001	163	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041002	151	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101011002	563	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041005	82	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041006	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041003	104	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101021002	148	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031001	303	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031002	171	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101021001	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031004	161	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031005	180	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071002	193	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071003	113	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071004	96	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041004	159	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071006	411	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071007	213	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041007	86	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101051001	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101051002	30	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101061001	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031003	98	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101061003	63	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071001	56	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092005	66	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092006	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092009	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071005	120	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092019	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092020	41	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081001	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081002	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081003	62	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081004	157	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101061002	92	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081006	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101091001	19	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102002	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102015	23	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102021	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092016	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102030	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102033	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092032	54	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092901	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101001	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101002	73	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081005	97	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101004	149	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101005	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101142011	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101991999	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102901	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102029	6	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101003	169	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101122001	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12102	12102012901	5	2017	NA	NA	NA	NA	NA	NA
12102	12102012012	1	2017	NA	NA	NA	NA	NA	NA
12102	12102012014	3	2017	NA	NA	NA	NA	NA	NA
12102	12102012015	1	2017	NA	NA	NA	NA	NA	NA
12102	12102012017	4	2017	NA	NA	NA	NA	NA	NA
12102	12102012020	2	2017	NA	NA	NA	NA	NA	NA
12103	12103012014	1	2017	NA	NA	NA	NA	NA	NA
12103	12103012019	1	2017	NA	NA	NA	NA	NA	NA
12103	12103022009	1	2017	NA	NA	NA	NA	NA	NA
12104	12104012008	1	2017	NA	NA	NA	NA	NA	NA
12104	12104012010	2	2017	NA	NA	NA	NA	NA	NA
12104	12104022901	1	2017	NA	NA	NA	NA	NA	NA
12201	12201011001	140	2017	NA	NA	NA	NA	NA	NA
12201	12201012901	2	2017	NA	NA	NA	NA	NA	NA
12301	12301012005	2	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301012007	5	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301032003	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301032011	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301012008	3	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301011001	61	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301011002	87	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301022001	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12302	12302012005	15	2017	NA	NA	NA	NA	NA	NA
12302	12302012901	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012005	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012009	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012901	3	2017	NA	NA	NA	NA	NA	NA
12303	12303012012	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012010	1	2017	NA	NA	NA	NA	NA	NA
12401	12401011001	68	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011002	154	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011003	63	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011005	65	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011006	89	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011007	80	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011008	196	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401012010	3	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401012017	1	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401012022	1	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401022013	1	2017	Natales	319416.8	2017	12401	21477	6860114515

4 Proporción poblacional zonal respecto a la comunal

Del censo obtenemos la cantidad de población a nivel de zona y estimamos su proporción a nivel comunal. Ya hemos calculado ésta proporción aquí.

prop_pob <- readRDS("tabla_de_prop_pob.rds")
names(prop_pob)[1] <- "zona"
names(prop_pob)[3] <- "p_poblacional" 

Veamos los 100 primeros registros:

r3_100 <- prop_pob[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	Freq	p_poblacional	código
1101011001	2491	0.0130100	01101
1101011002	1475	0.0077036	01101
1101021001	1003	0.0052385	01101
1101021002	54	0.0002820	01101
1101021003	2895	0.0151200	01101
1101021004	2398	0.0125243	01101
1101021005	4525	0.0236332	01101
1101031001	2725	0.0142321	01101
1101031002	3554	0.0185618	01101
1101031003	5246	0.0273988	01101
1101031004	3389	0.0177001	01101
1101041001	1800	0.0094010	01101
1101041002	2538	0.0132555	01101
1101041003	3855	0.0201339	01101
1101041004	5663	0.0295767	01101
1101041005	4162	0.0217373	01101
1101041006	2689	0.0140441	01101
1101051001	3296	0.0172144	01101
1101051002	4465	0.0233198	01101
1101051003	4656	0.0243174	01101
1101051004	2097	0.0109522	01101
1101051005	3569	0.0186402	01101
1101051006	2741	0.0143157	01101
1101061001	1625	0.0084871	01101
1101061002	4767	0.0248971	01101
1101061003	4826	0.0252053	01101
1101061004	4077	0.0212934	01101
1101061005	2166	0.0113126	01101
1101071001	2324	0.0121378	01101
1101071002	2801	0.0146291	01101
1101071003	3829	0.0199981	01101
1101071004	1987	0.0103777	01101
1101081001	5133	0.0268087	01101
1101081002	3233	0.0168853	01101
1101081003	2122	0.0110828	01101
1101081004	2392	0.0124929	01101
1101092001	57	0.0002977	01101
1101092004	247	0.0012900	01101
1101092005	76	0.0003969	01101
1101092006	603	0.0031494	01101
1101092007	84	0.0004387	01101
1101092010	398	0.0020787	01101
1101092012	58	0.0003029	01101
1101092014	23	0.0001201	01101
1101092016	20	0.0001045	01101
1101092017	8	0.0000418	01101
1101092018	74	0.0003865	01101
1101092019	25	0.0001306	01101
1101092021	177	0.0009244	01101
1101092022	23	0.0001201	01101
1101092023	288	0.0015042	01101
1101092024	14	0.0000731	01101
1101092901	30	0.0001567	01101
1101101001	2672	0.0139553	01101
1101101002	4398	0.0229699	01101
1101101003	4524	0.0236280	01101
1101101004	3544	0.0185096	01101
1101101005	4911	0.0256492	01101
1101101006	3688	0.0192617	01101
1101111001	3886	0.0202958	01101
1101111002	2312	0.0120751	01101
1101111003	4874	0.0254560	01101
1101111004	4543	0.0237272	01101
1101111005	4331	0.0226200	01101
1101111006	3253	0.0169898	01101
1101111007	4639	0.0242286	01101
1101111008	4881	0.0254925	01101
1101111009	5006	0.0261454	01101
1101111010	366	0.0019115	01101
1101111011	4351	0.0227244	01101
1101111012	2926	0.0152819	01101
1101111013	3390	0.0177053	01101
1101111014	2940	0.0153550	01101
1101112003	33	0.0001724	01101
1101112013	104	0.0005432	01101
1101112019	34	0.0001776	01101
1101112025	21	0.0001097	01101
1101112901	6	0.0000313	01101
1101991999	1062	0.0055466	01101
1107011001	4104	0.0378685	01107
1107011002	4360	0.0402307	01107
1107011003	8549	0.0788835	01107
1107012003	3	0.0000277	01107
1107012901	17	0.0001569	01107
1107021001	6701	0.0618316	01107
1107021002	3971	0.0366413	01107
1107021003	6349	0.0585836	01107
1107021004	5125	0.0472895	01107
1107021005	4451	0.0410704	01107
1107021006	3864	0.0356540	01107
1107021007	5235	0.0483045	01107
1107021008	4566	0.0421315	01107
1107031001	4195	0.0387082	01107
1107031002	7099	0.0655040	01107
1107031003	4720	0.0435525	01107
1107032005	38	0.0003506	01107
1107032006	2399	0.0221361	01107
1107032008	4	0.0000369	01107
1107041001	3630	0.0334948	01107
1107041002	5358	0.0494394	01107

5 Ingreso medio

Deseamos el valor del ingreso promedio a nivel comunal, pero expandido a nivel zonal. Ésta información está contenida en el campo promedio_i de la tabla obtenida en el punto 3.

r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	zona	Freq	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
12101	12101011004	162	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101011001	108	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101011003	125	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041001	163	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041002	151	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101011002	563	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041005	82	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041006	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041003	104	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101021002	148	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031001	303	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031002	171	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101021001	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031004	161	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031005	180	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071002	193	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071003	113	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071004	96	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041004	159	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071006	411	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071007	213	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101041007	86	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101051001	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101051002	30	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101061001	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101031003	98	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101061003	63	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071001	56	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092005	66	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092006	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092009	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101071005	120	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092019	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092020	41	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081001	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081002	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081003	62	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081004	157	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101061002	92	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081006	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101091001	19	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102002	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102015	23	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102021	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092016	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102030	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102033	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092032	54	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101092901	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101001	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101002	73	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101081005	97	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101004	149	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101005	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101142011	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101991999	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102901	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101102029	6	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101101003	169	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12101	12101122001	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598
12102	12102012901	5	2017	NA	NA	NA	NA	NA	NA
12102	12102012012	1	2017	NA	NA	NA	NA	NA	NA
12102	12102012014	3	2017	NA	NA	NA	NA	NA	NA
12102	12102012015	1	2017	NA	NA	NA	NA	NA	NA
12102	12102012017	4	2017	NA	NA	NA	NA	NA	NA
12102	12102012020	2	2017	NA	NA	NA	NA	NA	NA
12103	12103012014	1	2017	NA	NA	NA	NA	NA	NA
12103	12103012019	1	2017	NA	NA	NA	NA	NA	NA
12103	12103022009	1	2017	NA	NA	NA	NA	NA	NA
12104	12104012008	1	2017	NA	NA	NA	NA	NA	NA
12104	12104012010	2	2017	NA	NA	NA	NA	NA	NA
12104	12104022901	1	2017	NA	NA	NA	NA	NA	NA
12201	12201011001	140	2017	NA	NA	NA	NA	NA	NA
12201	12201012901	2	2017	NA	NA	NA	NA	NA	NA
12301	12301012005	2	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301012007	5	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301032003	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301032011	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301012008	3	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301011001	61	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301011002	87	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12301	12301022001	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224
12302	12302012005	15	2017	NA	NA	NA	NA	NA	NA
12302	12302012901	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012005	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012009	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012901	3	2017	NA	NA	NA	NA	NA	NA
12303	12303012012	1	2017	NA	NA	NA	NA	NA	NA
12303	12303012010	1	2017	NA	NA	NA	NA	NA	NA
12401	12401011001	68	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011002	154	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011003	63	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011005	65	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011006	89	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011007	80	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401011008	196	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401012010	3	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401012017	1	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401012022	1	2017	Natales	319416.8	2017	12401	21477	6860114515
12401	12401022013	1	2017	Natales	319416.8	2017	12401	21477	6860114515

6 Ingreso promedio expandido por zona (multi_pob)

En éste momento vamos a construir nuestra variable dependiente de regresión aplicando la siguiente fórmula:

\[ multi\_pob = promedio\_i \cdot personas \cdot p\_poblacional \]

Para ello integramos a la tabla de ingresos expandidos a nivel zonal (punto 3) la tabla de proporciones poblacionales zonales respecto al total comunal (punto 4) :

h_y_m_comuna_corr_01 = merge( x = comunas_con_ing_exp, y = prop_pob, by = "zona", all.x = TRUE)
tablamadre <- head(h_y_m_comuna_corr_01,100)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y
12101011001	12101	108	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3531	0.0268329	12101
12101011002	12101	563	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3026	0.0229953	12101
12101011003	12101	125	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2985	0.0226837	12101
12101011004	12101	162	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1595	0.0121208	12101
12101021001	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2549	0.0193705	12101
12101021002	12101	148	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3389	0.0257538	12101
12101031001	12101	303	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2497	0.0189753	12101
12101031002	12101	171	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3363	0.0255563	12101
12101031003	12101	98	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3844	0.0292115	12101
12101031004	12101	161	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3035	0.0230637	12101
12101031005	12101	180	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2132	0.0162016	12101
12101041001	12101	163	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2931	0.0222734	12101
12101041002	12101	151	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3427	0.0260426	12101
12101041003	12101	104	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3021	0.0229573	12101
12101041004	12101	159	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	4652	0.0353517	12101
12101041005	12101	82	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3038	0.0230865	12101
12101041006	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2472	0.0187853	12101
12101041007	12101	86	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3294	0.0250319	12101
12101051001	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2180	0.0165664	12101
12101051002	12101	30	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1013	0.0076980	12101
12101061001	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2372	0.0180254	12101
12101061002	12101	92	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2905	0.0220758	12101
12101061003	12101	63	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2197	0.0166955	12101
12101071001	12101	56	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1765	0.0134127	12101
12101071002	12101	193	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3727	0.0283224	12101
12101071003	12101	113	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2859	0.0217262	12101
12101071004	12101	96	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2382	0.0181014	12101
12101071005	12101	120	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3151	0.0239452	12101
12101071006	12101	411	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3159	0.0240060	12101
12101071007	12101	213	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3543	0.0269241	12101
12101081001	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2522	0.0191653	12101
12101081002	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3136	0.0238312	12101
12101081003	12101	62	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2280	0.0173263	12101
12101081004	12101	157	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	6468	0.0491519	12101
12101081005	12101	97	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3165	0.0240516	12101
12101081006	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5200	0.0395161	12101
12101091001	12101	19	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	692	0.0052587	12101
12101092005	12101	66	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	671	0.0050991	12101
12101092006	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101
12101092009	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	95	0.0007219	12101
12101092016	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101
12101092019	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1186	0.0090127	12101
12101092020	12101	41	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	491	0.0037312	12101
12101092032	12101	54	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1064	0.0080856	12101
12101092901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	19	0.0001444	12101
12101101001	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	205	0.0015578	12101
12101101002	12101	73	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1386	0.0105326	12101
12101101003	12101	169	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3937	0.0299182	12101
12101101004	12101	149	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5280	0.0401240	12101
12101101005	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3098	0.0235425	12101
12101102002	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	180	0.0013679	12101
12101102015	12101	23	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	252	0.0019150	12101
12101102021	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	567	0.0043088	12101
12101102029	12101	6	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	76	0.0005775	12101
12101102030	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	85	0.0006459	12101
12101102033	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	116	0.0008815	12101
12101102901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	59	0.0004484	12101
12101122001	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	184	0.0013983	12101
12101142011	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	217	0.0016490	12101
12101991999	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2529	0.0192185	12101
12102012012	12102	1	2017	NA	NA	NA	NA	NA	NA	13	0.0474453	12102
12102012014	12102	3	2017	NA	NA	NA	NA	NA	NA	19	0.0693431	12102
12102012015	12102	1	2017	NA	NA	NA	NA	NA	NA	9	0.0328467	12102
12102012017	12102	4	2017	NA	NA	NA	NA	NA	NA	35	0.1277372	12102
12102012020	12102	2	2017	NA	NA	NA	NA	NA	NA	115	0.4197080	12102
12102012901	12102	5	2017	NA	NA	NA	NA	NA	NA	70	0.2554745	12102
12103012014	12103	1	2017	NA	NA	NA	NA	NA	NA	51	0.0826580	12103
12103012019	12103	1	2017	NA	NA	NA	NA	NA	NA	122	0.1977310	12103
12103022009	12103	1	2017	NA	NA	NA	NA	NA	NA	272	0.4408428	12103
12104012008	12104	1	2017	NA	NA	NA	NA	NA	NA	30	0.0375469	12104
12104012010	12104	2	2017	NA	NA	NA	NA	NA	NA	313	0.3917397	12104
12104022901	12104	1	2017	NA	NA	NA	NA	NA	NA	52	0.0650814	12104
12201011001	12201	140	2017	NA	NA	NA	NA	NA	NA	1868	0.9054775	12201
12201012901	12201	2	2017	NA	NA	NA	NA	NA	NA	44	0.0213282	12201
12301011001	12301	61	2017	Porvenir	413917.4	2017	12301	6801	2815052224	2543	0.3739156	12301
12301011002	12301	87	2017	Porvenir	413917.4	2017	12301	6801	2815052224	3449	0.5071313	12301
12301012005	12301	2	2017	Porvenir	413917.4	2017	12301	6801	2815052224	14	0.0020585	12301
12301012007	12301	5	2017	Porvenir	413917.4	2017	12301	6801	2815052224	112	0.0164682	12301
12301012008	12301	3	2017	Porvenir	413917.4	2017	12301	6801	2815052224	74	0.0108808	12301
12301022001	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	23	0.0033819	12301
12301032003	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	62	0.0091163	12301
12301032011	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	285	0.0419056	12301
12302012005	12302	15	2017	NA	NA	NA	NA	NA	NA	795	0.6865285	12302
12302012901	12302	1	2017	NA	NA	NA	NA	NA	NA	109	0.0941278	12302
12303012005	12303	1	2017	NA	NA	NA	NA	NA	NA	70	0.1728395	12303
12303012009	12303	1	2017	NA	NA	NA	NA	NA	NA	22	0.0543210	12303
12303012010	12303	1	2017	NA	NA	NA	NA	NA	NA	100	0.2469136	12303
12303012012	12303	1	2017	NA	NA	NA	NA	NA	NA	19	0.0469136	12303
12303012901	12303	3	2017	NA	NA	NA	NA	NA	NA	29	0.0716049	12303
12401011001	12401	68	2017	Natales	319416.8	2017	12401	21477	6860114515	1266	0.0589468	12401
12401011002	12401	154	2017	Natales	319416.8	2017	12401	21477	6860114515	1994	0.0928435	12401
12401011003	12401	63	2017	Natales	319416.8	2017	12401	21477	6860114515	1327	0.0617870	12401
12401011004	12401	103	2017	Natales	319416.8	2017	12401	21477	6860114515	3053	0.1421521	12401
12401011005	12401	65	2017	Natales	319416.8	2017	12401	21477	6860114515	2710	0.1261815	12401
12401011006	12401	89	2017	Natales	319416.8	2017	12401	21477	6860114515	2158	0.1004796	12401
12401011007	12401	80	2017	Natales	319416.8	2017	12401	21477	6860114515	1489	0.0693300	12401
12401011008	12401	196	2017	Natales	319416.8	2017	12401	21477	6860114515	3985	0.1855473	12401
12401012010	12401	3	2017	Natales	319416.8	2017	12401	21477	6860114515	102	0.0047493	12401
12401012017	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	39	0.0018159	12401
12401012022	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	185	0.0086139	12401

Hacemos la multiplicación que queda almacenada en la variable multi_pob:

h_y_m_comuna_corr_01$multi_pob <- h_y_m_comuna_corr_01$promedio_i * h_y_m_comuna_corr_01$personas * h_y_m_comuna_corr_01$p_poblacional
tablamadre <- head(h_y_m_comuna_corr_01,100)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob
12101011001	12101	108	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3531	0.0268329	12101	1290980381
12101011002	12101	563	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3026	0.0229953	12101	1106345690
12101011003	12101	125	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2985	0.0226837	12101	1091355547
12101011004	12101	162	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1595	0.0121208	12101	583153131
12101021001	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2549	0.0193705	12101	931948170
12101021002	12101	148	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3389	0.0257538	12101	1239063299
12101031001	12101	303	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2497	0.0189753	12101	912936282
12101031002	12101	171	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3363	0.0255563	12101	1229557355
12101031003	12101	98	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3844	0.0292115	12101	1405417327
12101031004	12101	161	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3035	0.0230637	12101	1109636209
12101031005	12101	180	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2132	0.0162016	12101	779487446
12101041001	12101	163	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2931	0.0222734	12101	1071612431
12101041002	12101	151	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3427	0.0260426	12101	1252956603
12101041003	12101	104	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3021	0.0229573	12101	1104517624
12101041004	12101	159	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	4652	0.0353517	12101	1700832832
12101041005	12101	82	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3038	0.0230865	12101	1110733049
12101041006	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2472	0.0187853	12101	903795950
12101041007	12101	86	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3294	0.0250319	12101	1204330041
12101051001	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2180	0.0165664	12101	797036882
12101051002	12101	30	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1013	0.0076980	12101	370366221
12101061001	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2372	0.0180254	12101	867234625
12101061002	12101	92	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2905	0.0220758	12101	1062106487
12101061003	12101	63	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2197	0.0166955	12101	803252307
12101071001	12101	56	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1765	0.0134127	12101	645307384
12101071002	12101	193	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3727	0.0283224	12101	1362640577
12101071003	12101	113	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2859	0.0217262	12101	1045288278
12101071004	12101	96	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2382	0.0181014	12101	870890758
12101071005	12101	120	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3151	0.0239452	12101	1152047346
12101071006	12101	411	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3159	0.0240060	12101	1154972252
12101071007	12101	213	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3543	0.0269241	12101	1295367739
12101081001	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2522	0.0191653	12101	922076613
12101081002	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3136	0.0238312	12101	1146563147
12101081003	12101	62	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2280	0.0173263	12101	833598207
12101081004	12101	157	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	6468	0.0491519	12101	2364786491
12101081005	12101	97	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3165	0.0240516	12101	1157165932
12101081006	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5200	0.0395161	12101	1901188892
12101091001	12101	19	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	692	0.0052587	12101	253004368
12101092005	12101	66	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	671	0.0050991	12101	245326490
12101092006	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101	28883447
12101092009	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	95	0.0007219	12101	34733259
12101092016	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101	28883447
12101092019	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1186	0.0090127	12101	433617313
12101092020	12101	41	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	491	0.0037312	12101	179516105
12101092032	12101	54	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1064	0.0080856	12101	389012496
12101092901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	19	0.0001444	12101	6946652
12101101001	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	205	0.0015578	12101	74950716
12101101002	12101	73	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1386	0.0105326	12101	506739962
12101101003	12101	169	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3937	0.0299182	12101	1439419359
12101101004	12101	149	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5280	0.0401240	12101	1930437952
12101101005	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3098	0.0235425	12101	1132669844
12101102002	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	180	0.0013679	12101	65810385
12101102015	12101	23	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	252	0.0019150	12101	92134539
12101102021	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	567	0.0043088	12101	207302712
12101102029	12101	6	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	76	0.0005775	12101	27786607
12101102030	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	85	0.0006459	12101	31077126
12101102033	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	116	0.0008815	12101	42411137
12101102901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	59	0.0004484	12101	21571182
12101122001	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	184	0.0013983	12101	67272838
12101142011	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	217	0.0016490	12101	79338075
12101991999	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2529	0.0192185	12101	924635905
12102012012	12102	1	2017	NA	NA	NA	NA	NA	NA	13	0.0474453	12102	NA
12102012014	12102	3	2017	NA	NA	NA	NA	NA	NA	19	0.0693431	12102	NA
12102012015	12102	1	2017	NA	NA	NA	NA	NA	NA	9	0.0328467	12102	NA
12102012017	12102	4	2017	NA	NA	NA	NA	NA	NA	35	0.1277372	12102	NA
12102012020	12102	2	2017	NA	NA	NA	NA	NA	NA	115	0.4197080	12102	NA
12102012901	12102	5	2017	NA	NA	NA	NA	NA	NA	70	0.2554745	12102	NA
12103012014	12103	1	2017	NA	NA	NA	NA	NA	NA	51	0.0826580	12103	NA
12103012019	12103	1	2017	NA	NA	NA	NA	NA	NA	122	0.1977310	12103	NA
12103022009	12103	1	2017	NA	NA	NA	NA	NA	NA	272	0.4408428	12103	NA
12104012008	12104	1	2017	NA	NA	NA	NA	NA	NA	30	0.0375469	12104	NA
12104012010	12104	2	2017	NA	NA	NA	NA	NA	NA	313	0.3917397	12104	NA
12104022901	12104	1	2017	NA	NA	NA	NA	NA	NA	52	0.0650814	12104	NA
12201011001	12201	140	2017	NA	NA	NA	NA	NA	NA	1868	0.9054775	12201	NA
12201012901	12201	2	2017	NA	NA	NA	NA	NA	NA	44	0.0213282	12201	NA
12301011001	12301	61	2017	Porvenir	413917.4	2017	12301	6801	2815052224	2543	0.3739156	12301	1052591943
12301011002	12301	87	2017	Porvenir	413917.4	2017	12301	6801	2815052224	3449	0.5071313	12301	1427601106
12301012005	12301	2	2017	Porvenir	413917.4	2017	12301	6801	2815052224	14	0.0020585	12301	5794844
12301012007	12301	5	2017	Porvenir	413917.4	2017	12301	6801	2815052224	112	0.0164682	12301	46358749
12301012008	12301	3	2017	Porvenir	413917.4	2017	12301	6801	2815052224	74	0.0108808	12301	30629887
12301022001	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	23	0.0033819	12301	9520100
12301032003	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	62	0.0091163	12301	25662879
12301032011	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	285	0.0419056	12301	117966458
12302012005	12302	15	2017	NA	NA	NA	NA	NA	NA	795	0.6865285	12302	NA
12302012901	12302	1	2017	NA	NA	NA	NA	NA	NA	109	0.0941278	12302	NA
12303012005	12303	1	2017	NA	NA	NA	NA	NA	NA	70	0.1728395	12303	NA
12303012009	12303	1	2017	NA	NA	NA	NA	NA	NA	22	0.0543210	12303	NA
12303012010	12303	1	2017	NA	NA	NA	NA	NA	NA	100	0.2469136	12303	NA
12303012012	12303	1	2017	NA	NA	NA	NA	NA	NA	19	0.0469136	12303	NA
12303012901	12303	3	2017	NA	NA	NA	NA	NA	NA	29	0.0716049	12303	NA
12401011001	12401	68	2017	Natales	319416.8	2017	12401	21477	6860114515	1266	0.0589468	12401	404381663
12401011002	12401	154	2017	Natales	319416.8	2017	12401	21477	6860114515	1994	0.0928435	12401	636917090
12401011003	12401	63	2017	Natales	319416.8	2017	12401	21477	6860114515	1327	0.0617870	12401	423866087
12401011004	12401	103	2017	Natales	319416.8	2017	12401	21477	6860114515	3053	0.1421521	12401	975179476
12401011005	12401	65	2017	Natales	319416.8	2017	12401	21477	6860114515	2710	0.1261815	12401	865619516
12401011006	12401	89	2017	Natales	319416.8	2017	12401	21477	6860114515	2158	0.1004796	12401	689301444
12401011007	12401	80	2017	Natales	319416.8	2017	12401	21477	6860114515	1489	0.0693300	12401	475611608
12401011008	12401	196	2017	Natales	319416.8	2017	12401	21477	6860114515	3985	0.1855473	12401	1272875930
12401012010	12401	3	2017	Natales	319416.8	2017	12401	21477	6860114515	102	0.0047493	12401	32580513
12401012017	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	39	0.0018159	12401	12457255
12401012022	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	185	0.0086139	12401	59092107

7 Análisis de regresión

Aplicaremos un análisis de regresión donde:

\[ Y(dependiente) = ingreso \ expandido \ por \ zona \ (multi\_pob)\]

\[ X(independiente) = frecuencia \ de \ población \ que \ posee \ la \ variable \ Censal \ respecto \ a \ la \ zona \ (Freq.x) \]

7.1 Diagrama de dispersión

scatter.smooth(x=h_y_m_comuna_corr_01$Freq.x, y=h_y_m_comuna_corr_01$multi_pob, main="multi_pob ~ Freq.x",
     xlab = "Freq.x",
     ylab = "multi_pob",
           col = 2) 

7.2 Outliers

Hemos demostrado en el punto 5.7.2 de aquí que la exclusión de ouliers no genera ninguna mejora en el modelo de regresión.

7.3 Modelo lineal

Aplicaremos un análisis de regresión lineal del ingreso expandido por zona sobre las frecuencias de respuestas zonales.

linearMod <- lm( multi_pob~(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.458e+09 -3.341e+08 -1.191e+08  2.543e+08  1.393e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 355634881   64242300   5.536 3.63e-07 ***
## Freq.x        3922256     519786   7.546 5.50e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.35e+08 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.4098, Adjusted R-squared:  0.4026 
## F-statistic: 56.94 on 1 and 82 DF,  p-value: 5.503e-11

7.4 Gráfica de la recta de regresión lineal

ggplot(h_y_m_comuna_corr_01, aes(x = Freq.x , y = multi_pob)) + 
  geom_point() +
  stat_smooth(method = "lm", col = "red")

Si bien obtenemos nuestro modelo lineal da cuenta del 0.8214 de la variabilidad de los datos de respuesta en torno a su media, modelos alternativos pueden ofrecernos una explicación de la variable dependiente aún mayor.

8 Modelos alternativos

8.1 Modelo cuadrático

\[ \hat Y = \beta_0 + \beta_1 X^2 \]

linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^2), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.458e+09 -3.341e+08 -1.191e+08  2.543e+08  1.393e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 355634881   64242300   5.536 3.63e-07 ***
## Freq.x        3922256     519786   7.546 5.50e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.35e+08 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.4098, Adjusted R-squared:  0.4026 
## F-statistic: 56.94 on 1 and 82 DF,  p-value: 5.503e-11

8.2 Modelo cúbico

\[ \hat Y = \beta_0 + \beta_1 X^3 \]

linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^3), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.458e+09 -3.341e+08 -1.191e+08  2.543e+08  1.393e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 355634881   64242300   5.536 3.63e-07 ***
## Freq.x        3922256     519786   7.546 5.50e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.35e+08 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.4098, Adjusted R-squared:  0.4026 
## F-statistic: 56.94 on 1 and 82 DF,  p-value: 5.503e-11

8.3 Modelo logarítmico

\[ \hat Y = \beta_0 + \beta_1 ln X \]

linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -620257449 -267953535    2901908  173207878 1293716053 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -127869060   78457985   -1.63    0.107    
## log(Freq.x)  237120493   20142878   11.77   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 345300000 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.6 on 1 and 82 DF,  p-value: < 2.2e-16

8.4 Modelo exponencial

\[ \hat Y = \beta_0 + \beta_1 e^X \]

No es aplicable sin una transformación pues los valores elevados a \(e\) de Freq.x tienden a infinito.

8.5 Modelo con raíz cuadrada

\[ \hat Y = \beta_0 + \beta_1 \sqrt {X} \]

linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -1.016e+09 -1.598e+08 -4.375e+07  1.370e+08  1.247e+09 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -5841996   69611602  -0.084    0.933    
## sqrt(Freq.x) 89694630    7627749  11.759   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 345500000 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6232 
## F-statistic: 138.3 on 1 and 82 DF,  p-value: < 2.2e-16

8.6 Modelo raíz-raíz

\[ \hat Y = {\beta_0}^2 + 2 \beta_0 \beta_1 \sqrt{X}+ \beta_1^2 X \]

linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -24415.2  -4208.9   -609.8   4439.7  20486.1 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    6161.2     1390.4   4.431 2.88e-05 ***
## sqrt(Freq.x)   2171.1      152.4  14.250  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6901 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.7123, Adjusted R-squared:  0.7088 
## F-statistic: 203.1 on 1 and 82 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

\[ \hat Y = e^{\beta_0 + \beta_1 \sqrt{X}} \]

linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.1766 -0.4843  0.2125  0.6906  2.7355 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  17.42975    0.19099   91.26   <2e-16 ***
## sqrt(Freq.x)  0.27694    0.02093   13.23   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9479 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.6811, Adjusted R-squared:  0.6772 
## F-statistic: 175.1 on 1 and 82 DF,  p-value: < 2.2e-16

8.8 Modelo raíz-log

\[ \hat Y = {\beta_0}^2 + 2 \beta_0 \beta_1 \ln{X}+ \beta_1^2 ln^2X \]

linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11768.4  -4911.3    880.3   3110.9  21424.1 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2427.2     1399.9   1.734   0.0867 .  
## log(Freq.x)   5968.1      359.4  16.606   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6160 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.7708, Adjusted R-squared:  0.768 
## F-statistic: 275.8 on 1 and 82 DF,  p-value: < 2.2e-16

8.9 Modelo log-log

\[ \hat Y = e^{\beta_0+\beta_1 ln{X}} \]

linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.8364 -0.4097  0.1100  0.4108  2.9503 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 16.81323    0.16248  103.48   <2e-16 ***
## log(Freq.x)  0.80231    0.04171   19.23   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.715 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.8186, Adjusted R-squared:  0.8163 
## F-statistic: 369.9 on 1 and 82 DF,  p-value: < 2.2e-16

9 Modelo log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.8163).

9.1 Diagrama de dispersión sobre log-log

Desplegamos una curva suavizada por loess en el diagrama de dispersión.

scatter.smooth(x=log(h_y_m_comuna_corr_01$Freq.x), y=log(h_y_m_comuna_corr_01$multi_pob), lpars = list(col = "red", lwd = 2, lty = 1), main="multi_pob ~ Freq.x")

9.2 Modelo log-log

Observemos nuevamente el resultado sobre log-log.

linearMod <- lm(log( multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.8364 -0.4097  0.1100  0.4108  2.9503 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 16.81323    0.16248  103.48   <2e-16 ***
## log(Freq.x)  0.80231    0.04171   19.23   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.715 on 82 degrees of freedom
##   (22 observations deleted due to missingness)
## Multiple R-squared:  0.8186, Adjusted R-squared:  0.8163 
## F-statistic: 369.9 on 1 and 82 DF,  p-value: < 2.2e-16

ggplot(h_y_m_comuna_corr_01, aes(x = log(Freq.x) , y = log(multi_pob))) + 
  geom_point() +
  stat_smooth(method = "lm", col = "red")

9.3 Análisis de residuos

par(mfrow = c (2,2))
plot(linearMod)

9.4 Ecuación del modelo

\[ \hat Y = e^{16.81323+0.80231 \cdot ln{X}} \]

10 Aplicación la regresión a los valores de la variable a nivel de zona

Esta nueva variable se llamará: est_ing

h_y_m_comuna_corr_01$est_ing <- exp(16.81323+0.80231 * log(h_y_m_comuna_corr_01$Freq.x)) 

r3_100 <- h_y_m_comuna_corr_01[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing
12101011001	12101	108	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3531	0.0268329	12101	1290980381	857687785
12101011002	12101	563	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3026	0.0229953	12101	1106345690	3225918583
12101011003	12101	125	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2985	0.0226837	12101	1091355547	964417061
12101011004	12101	162	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1595	0.0121208	12101	583153131	1187432697
12101021001	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2549	0.0193705	12101	931948170	1038018970
12101021002	12101	148	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3389	0.0257538	12101	1239063299	1104372767
12101031001	12101	303	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2497	0.0189753	12101	912936282	1962362550
12101031002	12101	171	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3363	0.0255563	12101	1229557355	1240075483
12101031003	12101	98	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3844	0.0292115	12101	1405417327	793366037
12101031004	12101	161	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3035	0.0230637	12101	1109636209	1181548302
12101031005	12101	180	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2132	0.0162016	12101	779487446	1292173099
12101041001	12101	163	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2931	0.0222734	12101	1071612431	1193309914
12101041002	12101	151	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3427	0.0260426	12101	1252956603	1122297529
12101041003	12101	104	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3021	0.0229573	12101	1104517624	832106722
12101041004	12101	159	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	4652	0.0353517	12101	1700832832	1169757770
12101041005	12101	82	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3038	0.0230865	12101	1110733049	687646131
12101041006	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2472	0.0187853	12101	903795950	640137713
12101041007	12101	86	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3294	0.0250319	12101	1204330041	714431285
12101051001	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2180	0.0165664	12101	797036882	707758527
12101051002	12101	30	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1013	0.0076980	12101	370366221	306903729
12101061001	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2372	0.0180254	12101	867234625	640137713
12101061002	12101	92	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2905	0.0220758	12101	1062106487	754153279
12101061003	12101	63	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2197	0.0166955	12101	803252307	556572736
12101071001	12101	56	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1765	0.0134127	12101	645307384	506386067
12101071002	12101	193	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3727	0.0283224	12101	1362640577	1366527880
12101071003	12101	113	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2859	0.0217262	12101	1045288278	889402566
12101071004	12101	96	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2382	0.0181014	12101	870890758	780349300
12101071005	12101	120	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3151	0.0239452	12101	1152047346	933342232
12101071006	12101	411	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3159	0.0240060	12101	1154972252	2506134898
12101071007	12101	213	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3543	0.0269241	12101	1295367739	1479024103
12101081001	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2522	0.0191653	12101	922076613	694366174
12101081002	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3136	0.0238312	12101	1146563147	694366174
12101081003	12101	62	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2280	0.0173263	12101	833598207	549473546
12101081004	12101	157	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	6468	0.0491519	12101	2364786491	1157937882
12101081005	12101	97	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3165	0.0240516	12101	1157165932	786864300
12101081006	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5200	0.0395161	12101	1901188892	1038018970
12101091001	12101	19	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	692	0.0052587	12101	253004368	212740323
12101092005	12101	66	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	671	0.0050991	12101	245326490	577738497
12101092006	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101	28883447	34947200
12101092009	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	95	0.0007219	12101	34733259	60944113
12101092016	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101	28883447	95482465
12101092019	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1186	0.0090127	12101	433617313	256596243
12101092020	12101	41	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	491	0.0037312	12101	179516105	394317115
12101092032	12101	54	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1064	0.0080856	12101	389012496	491824149
12101092901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	19	0.0001444	12101	6946652	20039783
12101101001	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	205	0.0015578	12101	74950716	34947200
12101101002	12101	73	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1386	0.0105326	12101	506739962	626405520
12101101003	12101	169	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3937	0.0299182	12101	1439419359	1228425418
12101101004	12101	149	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5280	0.0401240	12101	1930437952	1110355599
12101101005	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3098	0.0235425	12101	1132669844	707758527
12101102002	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	180	0.0013679	12101	65810385	20039783
12101102015	12101	23	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	252	0.0019150	12101	92134539	247982408
12101102021	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	567	0.0043088	12101	207302712	256596243
12101102029	12101	6	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	76	0.0005775	12101	27786607	84374564
12101102030	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	85	0.0006459	12101	31077126	95482465
12101102033	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	116	0.0008815	12101	42411137	20039783
12101102901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	59	0.0004484	12101	21571182	20039783
12101122001	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	184	0.0013983	12101	67272838	60944113
12101142011	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	217	0.0016490	12101	79338075	48382930
12101991999	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2529	0.0192185	12101	924635905	48382930
12102012012	12102	1	2017	NA	NA	NA	NA	NA	NA	13	0.0474453	12102	NA	20039783
12102012014	12102	3	2017	NA	NA	NA	NA	NA	NA	19	0.0693431	12102	NA	48382930
12102012015	12102	1	2017	NA	NA	NA	NA	NA	NA	9	0.0328467	12102	NA	20039783
12102012017	12102	4	2017	NA	NA	NA	NA	NA	NA	35	0.1277372	12102	NA	60944113
12102012020	12102	2	2017	NA	NA	NA	NA	NA	NA	115	0.4197080	12102	NA	34947200
12102012901	12102	5	2017	NA	NA	NA	NA	NA	NA	70	0.2554745	12102	NA	72892633
12103012014	12103	1	2017	NA	NA	NA	NA	NA	NA	51	0.0826580	12103	NA	20039783
12103012019	12103	1	2017	NA	NA	NA	NA	NA	NA	122	0.1977310	12103	NA	20039783
12103022009	12103	1	2017	NA	NA	NA	NA	NA	NA	272	0.4408428	12103	NA	20039783
12104012008	12104	1	2017	NA	NA	NA	NA	NA	NA	30	0.0375469	12104	NA	20039783
12104012010	12104	2	2017	NA	NA	NA	NA	NA	NA	313	0.3917397	12104	NA	34947200
12104022901	12104	1	2017	NA	NA	NA	NA	NA	NA	52	0.0650814	12104	NA	20039783
12201011001	12201	140	2017	NA	NA	NA	NA	NA	NA	1868	0.9054775	12201	NA	1056216618
12201012901	12201	2	2017	NA	NA	NA	NA	NA	NA	44	0.0213282	12201	NA	34947200
12301011001	12301	61	2017	Porvenir	413917.4	2017	12301	6801	2815052224	2543	0.3739156	12301	1052591943	542351683
12301011002	12301	87	2017	Porvenir	413917.4	2017	12301	6801	2815052224	3449	0.5071313	12301	1427601106	721088723
12301012005	12301	2	2017	Porvenir	413917.4	2017	12301	6801	2815052224	14	0.0020585	12301	5794844	34947200
12301012007	12301	5	2017	Porvenir	413917.4	2017	12301	6801	2815052224	112	0.0164682	12301	46358749	72892633
12301012008	12301	3	2017	Porvenir	413917.4	2017	12301	6801	2815052224	74	0.0108808	12301	30629887	48382930
12301022001	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	23	0.0033819	12301	9520100	20039783
12301032003	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	62	0.0091163	12301	25662879	20039783
12301032011	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	285	0.0419056	12301	117966458	20039783
12302012005	12302	15	2017	NA	NA	NA	NA	NA	NA	795	0.6865285	12302	NA	175987892
12302012901	12302	1	2017	NA	NA	NA	NA	NA	NA	109	0.0941278	12302	NA	20039783
12303012005	12303	1	2017	NA	NA	NA	NA	NA	NA	70	0.1728395	12303	NA	20039783
12303012009	12303	1	2017	NA	NA	NA	NA	NA	NA	22	0.0543210	12303	NA	20039783
12303012010	12303	1	2017	NA	NA	NA	NA	NA	NA	100	0.2469136	12303	NA	20039783
12303012012	12303	1	2017	NA	NA	NA	NA	NA	NA	19	0.0469136	12303	NA	20039783
12303012901	12303	3	2017	NA	NA	NA	NA	NA	NA	29	0.0716049	12303	NA	48382930
12401011001	12401	68	2017	Natales	319416.8	2017	12401	21477	6860114515	1266	0.0589468	12401	404381663	591743148
12401011002	12401	154	2017	Natales	319416.8	2017	12401	21477	6860114515	1994	0.0928435	12401	636917090	1140152021
12401011003	12401	63	2017	Natales	319416.8	2017	12401	21477	6860114515	1327	0.0617870	12401	423866087	556572736
12401011004	12401	103	2017	Natales	319416.8	2017	12401	21477	6860114515	3053	0.1421521	12401	975179476	825681294
12401011005	12401	65	2017	Natales	319416.8	2017	12401	21477	6860114515	2710	0.1261815	12401	865619516	570704802
12401011006	12401	89	2017	Natales	319416.8	2017	12401	21477	6860114515	2158	0.1004796	12401	689301444	734358470
12401011007	12401	80	2017	Natales	319416.8	2017	12401	21477	6860114515	1489	0.0693300	12401	475611608	674157141
12401011008	12401	196	2017	Natales	319416.8	2017	12401	21477	6860114515	3985	0.1855473	12401	1272875930	1383544017
12401012010	12401	3	2017	Natales	319416.8	2017	12401	21477	6860114515	102	0.0047493	12401	32580513	48382930
12401012017	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	39	0.0018159	12401	12457255	20039783
12401012022	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	185	0.0086139	12401	59092107	20039783

11 División del valor estimado entre la población total de la zona para obtener el ingreso medio por zona

\[ Ingreso \_ Medio\_zona = est\_ing / (personas * p\_poblacional) \]

h_y_m_comuna_corr_01$ing_medio_zona <- h_y_m_comuna_corr_01$est_ing  /( h_y_m_comuna_corr_01$personas  * h_y_m_comuna_corr_01$p_poblacional)

r3_100 <- h_y_m_comuna_corr_01[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing	ing_medio_zona
12101011001	12101	108	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3531	0.0268329	12101	1290980381	857687785	242902.23
12101011002	12101	563	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3026	0.0229953	12101	1106345690	3225918583	1066066.95
12101011003	12101	125	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2985	0.0226837	12101	1091355547	964417061	323087.79
12101011004	12101	162	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1595	0.0121208	12101	583153131	1187432697	744471.91
12101021001	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2549	0.0193705	12101	931948170	1038018970	407225.96
12101021002	12101	148	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3389	0.0257538	12101	1239063299	1104372767	325869.80
12101031001	12101	303	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2497	0.0189753	12101	912936282	1962362550	785888.09
12101031002	12101	171	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3363	0.0255563	12101	1229557355	1240075483	368740.85
12101031003	12101	98	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3844	0.0292115	12101	1405417327	793366037	206390.75
12101031004	12101	161	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3035	0.0230637	12101	1109636209	1181548302	389307.51
12101031005	12101	180	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2132	0.0162016	12101	779487446	1292173099	606084.94
12101041001	12101	163	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2931	0.0222734	12101	1071612431	1193309914	407134.05
12101041002	12101	151	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3427	0.0260426	12101	1252956603	1122297529	327486.88
12101041003	12101	104	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3021	0.0229573	12101	1104517624	832106722	275440.82
12101041004	12101	159	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	4652	0.0353517	12101	1700832832	1169757770	251452.66
12101041005	12101	82	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3038	0.0230865	12101	1110733049	687646131	226348.30
12101041006	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2472	0.0187853	12101	903795950	640137713	258955.39
12101041007	12101	86	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3294	0.0250319	12101	1204330041	714431285	216888.67
12101051001	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2180	0.0165664	12101	797036882	707758527	324659.87
12101051002	12101	30	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1013	0.0076980	12101	370366221	306903729	302965.18
12101061001	12101	75	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2372	0.0180254	12101	867234625	640137713	269872.56
12101061002	12101	92	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2905	0.0220758	12101	1062106487	754153279	259605.26
12101061003	12101	63	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2197	0.0166955	12101	803252307	556572736	253333.06
12101071001	12101	56	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1765	0.0134127	12101	645307384	506386067	286904.29
12101071002	12101	193	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3727	0.0283224	12101	1362640577	1366527880	366656.26
12101071003	12101	113	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2859	0.0217262	12101	1045288278	889402566	311088.69
12101071004	12101	96	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2382	0.0181014	12101	870890758	780349300	327602.56
12101071005	12101	120	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3151	0.0239452	12101	1152047346	933342232	296205.09
12101071006	12101	411	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3159	0.0240060	12101	1154972252	2506134898	793331.72
12101071007	12101	213	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3543	0.0269241	12101	1295367739	1479024103	417449.65
12101081001	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2522	0.0191653	12101	922076613	694366174	275323.62
12101081002	12101	83	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3136	0.0238312	12101	1146563147	694366174	221417.79
12101081003	12101	62	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2280	0.0173263	12101	833598207	549473546	240997.17
12101081004	12101	157	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	6468	0.0491519	12101	2364786491	1157937882	179025.65
12101081005	12101	97	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3165	0.0240516	12101	1157165932	786864300	248614.31
12101081006	12101	137	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5200	0.0395161	12101	1901188892	1038018970	199619.03
12101091001	12101	19	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	692	0.0052587	12101	253004368	212740323	307428.21
12101092005	12101	66	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	671	0.0050991	12101	245326490	577738497	861011.17
12101092006	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101	28883447	34947200	442369.62
12101092009	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	95	0.0007219	12101	34733259	60944113	641516.98
12101092016	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	79	0.0006003	12101	28883447	95482465	1208638.79
12101092019	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1186	0.0090127	12101	433617313	256596243	216354.34
12101092020	12101	41	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	491	0.0037312	12101	179516105	394317115	803089.85
12101092032	12101	54	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1064	0.0080856	12101	389012496	491824149	462240.74
12101092901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	19	0.0001444	12101	6946652	20039783	1054725.41
12101101001	12101	2	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	205	0.0015578	12101	74950716	34947200	170474.15
12101101002	12101	73	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	1386	0.0105326	12101	506739962	626405520	451952.03
12101101003	12101	169	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3937	0.0299182	12101	1439419359	1228425418	312020.68
12101101004	12101	149	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	5280	0.0401240	12101	1930437952	1110355599	210294.62
12101101005	12101	85	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	3098	0.0235425	12101	1132669844	707758527	228456.59
12101102002	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	180	0.0013679	12101	65810385	20039783	111332.13
12101102015	12101	23	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	252	0.0019150	12101	92134539	247982408	984057.17
12101102021	12101	24	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	567	0.0043088	12101	207302712	256596243	452550.69
12101102029	12101	6	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	76	0.0005775	12101	27786607	84374564	1110191.63
12101102030	12101	7	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	85	0.0006459	12101	31077126	95482465	1123323.11
12101102033	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	116	0.0008815	12101	42411137	20039783	172756.75
12101102901	12101	1	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	59	0.0004484	12101	21571182	20039783	339657.34
12101122001	12101	4	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	184	0.0013983	12101	67272838	60944113	331218.01
12101142011	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	217	0.0016490	12101	79338075	48382930	222962.81
12101991999	12101	3	2017	Punta Arenas	365613.2	2017	12101	131592	48111778598	2529	0.0192185	12101	924635905	48382930	19131.25
12102012012	12102	1	2017	NA	NA	NA	NA	NA	NA	13	0.0474453	12102	NA	20039783	NA
12102012014	12102	3	2017	NA	NA	NA	NA	NA	NA	19	0.0693431	12102	NA	48382930	NA
12102012015	12102	1	2017	NA	NA	NA	NA	NA	NA	9	0.0328467	12102	NA	20039783	NA
12102012017	12102	4	2017	NA	NA	NA	NA	NA	NA	35	0.1277372	12102	NA	60944113	NA
12102012020	12102	2	2017	NA	NA	NA	NA	NA	NA	115	0.4197080	12102	NA	34947200	NA
12102012901	12102	5	2017	NA	NA	NA	NA	NA	NA	70	0.2554745	12102	NA	72892633	NA
12103012014	12103	1	2017	NA	NA	NA	NA	NA	NA	51	0.0826580	12103	NA	20039783	NA
12103012019	12103	1	2017	NA	NA	NA	NA	NA	NA	122	0.1977310	12103	NA	20039783	NA
12103022009	12103	1	2017	NA	NA	NA	NA	NA	NA	272	0.4408428	12103	NA	20039783	NA
12104012008	12104	1	2017	NA	NA	NA	NA	NA	NA	30	0.0375469	12104	NA	20039783	NA
12104012010	12104	2	2017	NA	NA	NA	NA	NA	NA	313	0.3917397	12104	NA	34947200	NA
12104022901	12104	1	2017	NA	NA	NA	NA	NA	NA	52	0.0650814	12104	NA	20039783	NA
12201011001	12201	140	2017	NA	NA	NA	NA	NA	NA	1868	0.9054775	12201	NA	1056216618	NA
12201012901	12201	2	2017	NA	NA	NA	NA	NA	NA	44	0.0213282	12201	NA	34947200	NA
12301011001	12301	61	2017	Porvenir	413917.4	2017	12301	6801	2815052224	2543	0.3739156	12301	1052591943	542351683	213272.39
12301011002	12301	87	2017	Porvenir	413917.4	2017	12301	6801	2815052224	3449	0.5071313	12301	1427601106	721088723	209071.82
12301012005	12301	2	2017	Porvenir	413917.4	2017	12301	6801	2815052224	14	0.0020585	12301	5794844	34947200	2496228.59
12301012007	12301	5	2017	Porvenir	413917.4	2017	12301	6801	2815052224	112	0.0164682	12301	46358749	72892633	650827.08
12301012008	12301	3	2017	Porvenir	413917.4	2017	12301	6801	2815052224	74	0.0108808	12301	30629887	48382930	653823.38
12301022001	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	23	0.0033819	12301	9520100	20039783	871294.91
12301032003	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	62	0.0091163	12301	25662879	20039783	323222.30
12301032011	12301	1	2017	Porvenir	413917.4	2017	12301	6801	2815052224	285	0.0419056	12301	117966458	20039783	70315.03
12302012005	12302	15	2017	NA	NA	NA	NA	NA	NA	795	0.6865285	12302	NA	175987892	NA
12302012901	12302	1	2017	NA	NA	NA	NA	NA	NA	109	0.0941278	12302	NA	20039783	NA
12303012005	12303	1	2017	NA	NA	NA	NA	NA	NA	70	0.1728395	12303	NA	20039783	NA
12303012009	12303	1	2017	NA	NA	NA	NA	NA	NA	22	0.0543210	12303	NA	20039783	NA
12303012010	12303	1	2017	NA	NA	NA	NA	NA	NA	100	0.2469136	12303	NA	20039783	NA
12303012012	12303	1	2017	NA	NA	NA	NA	NA	NA	19	0.0469136	12303	NA	20039783	NA
12303012901	12303	3	2017	NA	NA	NA	NA	NA	NA	29	0.0716049	12303	NA	48382930	NA
12401011001	12401	68	2017	Natales	319416.8	2017	12401	21477	6860114515	1266	0.0589468	12401	404381663	591743148	467411.65
12401011002	12401	154	2017	Natales	319416.8	2017	12401	21477	6860114515	1994	0.0928435	12401	636917090	1140152021	571791.38
12401011003	12401	63	2017	Natales	319416.8	2017	12401	21477	6860114515	1327	0.0617870	12401	423866087	556572736	419421.81
12401011004	12401	103	2017	Natales	319416.8	2017	12401	21477	6860114515	3053	0.1421521	12401	975179476	825681294	270449.16
12401011005	12401	65	2017	Natales	319416.8	2017	12401	21477	6860114515	2710	0.1261815	12401	865619516	570704802	210592.18
12401011006	12401	89	2017	Natales	319416.8	2017	12401	21477	6860114515	2158	0.1004796	12401	689301444	734358470	340295.86
12401011007	12401	80	2017	Natales	319416.8	2017	12401	21477	6860114515	1489	0.0693300	12401	475611608	674157141	452758.32
12401011008	12401	196	2017	Natales	319416.8	2017	12401	21477	6860114515	3985	0.1855473	12401	1272875930	1383544017	347187.96
12401012010	12401	3	2017	Natales	319416.8	2017	12401	21477	6860114515	102	0.0047493	12401	32580513	48382930	474342.45
12401012017	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	39	0.0018159	12401	12457255	20039783	513840.59
12401012022	12401	1	2017	Natales	319416.8	2017	12401	21477	6860114515	185	0.0086139	12401	59092107	20039783	108323.15

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "casen_censo_region_12.rds")

12 Referencias

https://rpubs.com/osoramirez/316691

https://dataintelligencechile.shinyapps.io/casenfinal

Manual_de_usuario_Censo_2017_16R.pdf

http://www.censo2017.cl/microdatos/

Censo de Población y Vivienda

https://www.ine.cl/estadisticas/sociales/censos-de-poblacion-y-vivienda/poblacion-y-vivienda

http://r-statistics.co/Linear-Regression.html