Data
Column
Enf[All.Acute] & PM2.5
Column
Componente.Princ 1 [J:00, J:02, J:03, J:20]
Predictor: PM2.5
Call:
glm(formula = enf.PC1 ~ PM2.5 + I(PM2.5^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.2781656 1.3924177 -2.354 0.0207 *
PM2.5 0.1643916 0.0707806 2.323 0.0224 *
I(PM2.5^2) -0.0017726 0.0008344 -2.124 0.0363 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 4.413727)
Null deviance: 435.56 on 95 degrees of freedom
Residual deviance: 410.48 on 93 degrees of freedom
AIC: 419.92
Number of Fisher Scoring iterations: 2Column
Modelo Unimodal: Componente 1 [J:00, J:02, J:03, J:20] ~ PM2.5
Enf[All.Acute_J:01,J:04,J:06,J:21,J:22] & SO2
Column
Componente.Princ 1 [J:01, J:04, J:06, J:21, J:22]
Predictor: SO2
Call:
glm(formula = enf.PC2 ~ SO2 + I(SO2^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.897037 0.256142 -3.502 0.000854 ***
SO2 0.371863 0.094728 3.926 0.000217 ***
I(SO2^2) -0.017976 0.006127 -2.934 0.004668 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.9755507)
Null deviance: 83.373 on 65 degrees of freedom
Residual deviance: 61.460 on 63 degrees of freedom
(30 observations deleted due to missingness)
AIC: 190.6
Number of Fisher Scoring iterations: 2Column
Modelo Unimodal: Componente 1 [J:01, J:04, J:06, J:21, J:22] ~ SO2
EnfJ:01 & SO2 + (NO2)^2
Column
J:01
Predictor: SO2 + (NO2)^2
Call:
glm(formula = J01 ~ SO2 + NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.6566437 0.2508429 10.591 < 2e-16 ***
SO2 0.0132218 0.0051738 2.556 0.01060 *
NO2 0.0427312 0.0133555 3.200 0.00138 **
I(NO2^2) -0.0005617 0.0001726 -3.255 0.00113 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 458.28 on 64 degrees of freedom
Residual deviance: 437.09 on 61 degrees of freedom
(31 observations deleted due to missingness)
AIC: 784.3
Number of Fisher Scoring iterations: 4Modelo Lineal: J:01 ~ SO2
Column
Modelo unimodal: J:01 ~ NO2
3D - J:01 ~ SO2 + (NO2)^2
Call:
glm(formula = J01 ~ NO2 + I(NO2^2) + SO2, family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.6566437 0.2508429 10.591 < 2e-16 ***
NO2 0.0427312 0.0133555 3.200 0.00138 **
I(NO2^2) -0.0005617 0.0001726 -3.255 0.00113 **
SO2 0.0132218 0.0051738 2.556 0.01060 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 458.28 on 64 degrees of freedom
Residual deviance: 437.09 on 61 degrees of freedom
(31 observations deleted due to missingness)
AIC: 784.3
Number of Fisher Scoring iterations: 4
EnfJ:04 & SO2 + (NO2)^2
Column
J:04
Predictor: SO2 + (NO2)^2
Call:
glm(formula = J04 ~ SO2 + NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.8267550 0.2350162 12.028 < 2e-16 ***
SO2 0.0155360 0.0048493 3.204 0.00136 **
NO2 0.0392781 0.0125245 3.136 0.00171 **
I(NO2^2) -0.0005171 0.0001619 -3.194 0.00140 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 319.02 on 64 degrees of freedom
Residual deviance: 293.62 on 61 degrees of freedom
(31 observations deleted due to missingness)
AIC: 650.45
Number of Fisher Scoring iterations: 4Modelo Lineal: J:04 ~ SO2
Column
Modelo unimodal: J:04 ~ NO2
Column
EnfJ:02 & SO2 + (NO2)^2 + (PM2.5)^2
Column
J:02
Predictor: SO2 + NO2 ^ 2 + PM2.5 ^ 2
Call:
glm(formula = J02 ~ PM2.5 + I(PM2.5^2) + SO2 + NO2 + I(NO2^2),
family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.032e+00 5.508e-02 91.36 <2e-16 ***
PM2.5 3.800e-02 1.893e-03 20.07 <2e-16 ***
I(PM2.5^2) -5.531e-04 2.456e-05 -22.52 <2e-16 ***
SO2 1.196e-02 1.017e-03 11.76 <2e-16 ***
NO2 6.181e-02 2.806e-03 22.03 <2e-16 ***
I(NO2^2) -8.154e-04 3.606e-05 -22.61 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 11995 on 64 degrees of freedom
Residual deviance: 10490 on 59 degrees of freedom
(31 observations deleted due to missingness)
AIC: 11054
Number of Fisher Scoring iterations: 4Modelo Lineal: J:02 ~ SO2
Column
Modelo unimodal: J:02 ~ NO2
Modelo unimodal: J:02 ~ PM2.5
Column
Enf[All.Acute] & NO2
Column
Componente.Princ 1 [J:00, J:02, J:03, J:20]
Predictor: NO2
Call:
glm(formula = enf.PC1 ~ NO2 + I(NO2^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.168226 1.979610 -2.611 0.0106 *
NO2 0.277979 0.109377 2.541 0.0127 *
I(NO2^2) -0.003436 0.001448 -2.372 0.0198 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 4.399807)
Null deviance: 430.78 on 93 degrees of freedom
Residual deviance: 400.38 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 410.98
Number of Fisher Scoring iterations: 2Column
Modelo Unimodal: Componente 1 [J:00, J:02, J:03, J:20] ~ NO2
Enf[All.Acute] & SO2
Column
Componente.Princ 1 [J:00, J:02, J:03, J:20]
Predictor: SO2
Call:
glm(formula = enf.PC1 ~ SO2, data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.67259 0.39458 1.705 0.0931 .
SO2 -0.03458 0.06230 -0.555 0.5808
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 4.573962)
Null deviance: 294.14 on 65 degrees of freedom
Residual deviance: 292.73 on 64 degrees of freedom
(30 observations deleted due to missingness)
AIC: 291.61
Number of Fisher Scoring iterations: 2NO2 ~ SO2
Call:
glm(formula = SO2 ~ NO2, data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.13790 1.92131 4.756 1.19e-05 ***
NO2 -0.11972 0.04944 -2.421 0.0184 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 16.8442)
Null deviance: 1159.9 on 64 degrees of freedom
Residual deviance: 1061.2 on 63 degrees of freedom
(31 observations deleted due to missingness)
AIC: 371.99
Number of Fisher Scoring iterations: 2Column
Modelo Unimodal: Componente 1 [J:00, J:02, J:03, J:20] ~ SO2
J:21 ~ SO2 & NO2
Column
Enf. Respiratoria [J:21]
Predictor: SO2 + NO2
Call:
glm(formula = J21 ~ SO2 + I(SO2^2) + NO2 + I(NO2^2), family = poisson,
data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.2168146 0.3071446 3.962 7.44e-05 ***
SO2 0.2313072 0.0221371 10.449 < 2e-16 ***
I(SO2^2) -0.0141242 0.0014384 -9.820 < 2e-16 ***
NO2 0.0671286 0.0155881 4.306 1.66e-05 ***
I(NO2^2) -0.0007123 0.0002003 -3.556 0.000377 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 920.86 on 64 degrees of freedom
Residual deviance: 795.95 on 60 degrees of freedom
(31 observations deleted due to missingness)
AIC: 1112.3
Number of Fisher Scoring iterations: 5Modelo Unimodal: J:21 ~ SO2
Column
Modelo Unimodal: J:21 ~ NO2
[1] "Peak of cases NO2 = 43.8 μg/m3"
J:22 ~ PM2.5 & SO2
Column
Enf. Respiratoria [J:22]
Predictor: PM2.5 + SO2
Call:
glm(formula = J22 ~ PM2.5 + I(PM2.5^2) + SO2 + I(SO2^2), family = poisson,
data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.6957071 0.2486214 2.798 0.00514 **
PM2.5 0.0863751 0.0115707 7.465 8.33e-14 ***
I(PM2.5^2) -0.0008477 0.0001381 -6.137 8.39e-10 ***
SO2 0.1669453 0.0223394 7.473 7.83e-14 ***
I(SO2^2) -0.0093895 0.0014382 -6.529 6.63e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1115.78 on 65 degrees of freedom
Residual deviance: 978.62 on 61 degrees of freedom
(30 observations deleted due to missingness)
AIC: 1276.8
Number of Fisher Scoring iterations: 5Column
Modelo Unimodal: J:22 ~ PM2.5
Column
Modelo Unimodal: J:22 ~ SO2
[1] "Peak of cases SO2 = 8.98 μg/m3"
J:00 ~ PM2.5
Column
Enf. Respiratoria [J:00]
Predictor: PM2.5
Shapiro-Wilk normality test
data: m1$J0
W = 0.98371, p-value = 0.2807
Call:
glm(formula = J0 ~ PM2.5 + I(PM2.5^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2069.6765 606.8088 3.411 0.00096 ***
PM2.5 78.3261 30.8458 2.539 0.01277 *
I(PM2.5^2) -0.8535 0.3636 -2.347 0.02104 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 838243.5)
Null deviance: 83558974 on 95 degrees of freedom
Residual deviance: 77956648 on 93 degrees of freedom
AIC: 1586.7
Number of Fisher Scoring iterations: 2Column
Modelo Unimodal: J:00 ~ PM2.5
J:03 ~ PM2.5
Column
Enf. Respiratoria J:02
Predictor: PM2.5
Shapiro-Wilk normality test
data: m1$J03
W = 0.94716, p-value = 0.000723
Call:
glm(formula = J03 ~ PM2.5 + I(PM2.5^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 6.818e+00 1.704e-02 400.00 <2e-16 ***
PM2.5 3.198e-02 8.580e-04 37.28 <2e-16 ***
I(PM2.5^2) -3.370e-04 1.013e-05 -33.27 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 24790 on 95 degrees of freedom
Residual deviance: 23179 on 93 degrees of freedom
AIC: 24072
Number of Fisher Scoring iterations: 4Column
Modelo Unimodal: J:02 ~ PM2.5
J:00 ~ NO2
Column
Enf. Respiratoria [J:00]
Predictor: NO2
Shapiro-Wilk normality test
data: m1$J0
W = 0.98371, p-value = 0.2807
Call:
glm(formula = J0 ~ NO2 + I(NO2^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1192.6046 865.9138 1.377 0.17180
NO2 133.1846 47.8431 2.784 0.00653 **
I(NO2^2) -1.6757 0.6335 -2.645 0.00962 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 841828.5)
Null deviance: 83328334 on 93 degrees of freedom
Residual deviance: 76606390 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 1554.2
Number of Fisher Scoring iterations: 2Column
Modelo Unimodal: J:00 ~ PM2.5
J:02 ~ NO2
Column
Enf. Respiratoria J:02
Predictor: NO2
Shapiro-Wilk normality test
data: m1$J02
W = 0.93817, p-value = 0.0002055
Call:
glm(formula = J02 ~ NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.792e+00 3.727e-02 155.41 <2e-16 ***
NO2 4.854e-02 2.046e-03 23.72 <2e-16 ***
I(NO2^2) -6.252e-04 2.708e-05 -23.08 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 16714 on 93 degrees of freedom
Residual deviance: 16113 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 16907
Number of Fisher Scoring iterations: 4Column
Modelo Unimodal: J:02 ~ PM2.5
J:03 ~ NO2
Column
Enf. Respiratoria [J:03]
Predictor: NO2
Shapiro-Wilk normality test
data: m1$J03
W = 0.94716, p-value = 0.000723
Call:
glm(formula = J03 ~ NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 6.701e+00 2.461e-02 272.26 <2e-16 ***
NO2 4.393e-02 1.355e-03 32.41 <2e-16 ***
I(NO2^2) -5.795e-04 1.799e-05 -32.21 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 24321 on 93 degrees of freedom
Residual deviance: 23204 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 24078
Number of Fisher Scoring iterations: 4Column
Modelo Unimodal: J:03 ~ PM2.5
J:06 ~ NO2
Column
Enf. Respiratoria [J:06]
Predictor: SO2, NO2
Call:
glm(formula = J06 ~ SO2 + +NO2 + I(NO2^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -308.2729 233.9980 -1.317 0.192626
SO2 -25.2919 5.4470 -4.643 1.87e-05 ***
NO2 48.8569 12.3498 3.956 0.000201 ***
I(NO2^2) -0.6019 0.1580 -3.811 0.000325 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 30944.81)
Null deviance: 3068443 on 64 degrees of freedom
Residual deviance: 1887633 on 61 degrees of freedom
(31 observations deleted due to missingness)
AIC: 862.43
Number of Fisher Scoring iterations: 2
Call:
glm(formula = J06 ~ NO2 + I(NO2^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.699 203.611 0.013 0.9895
NO2 23.441 11.250 2.084 0.0400 *
I(NO2^2) -0.269 0.149 -1.806 0.0742 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 46545.41)
Null deviance: 4516085 on 93 degrees of freedom
Residual deviance: 4235632 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 1282
Number of Fisher Scoring iterations: 2** El NO2 se asocia negativamente con el SO2. POr eso la asociación de la J06 con el SO2 parece ser “negativa”. Es decir, la asociación negativa con el SO2 es muy posiblmente coincidental, y la asociación positiva con el NO2 es a la que es más priudente ponerele atención.
Column
NO2 - SO2
Modelo Unimodal: J:06 ~ NO2
Column
Modelo Unimodal: J:06 ~ PM2.5
J:20 ~ SO2, NO2
Column
Enf. Respiratoria [J:20]
Predictor: SO2, NO2
Call:
glm(formula = J20 ~ SO2 + NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.830e+00 7.013e-02 68.86 <2e-16 ***
SO2 -2.427e-02 1.514e-03 -16.03 <2e-16 ***
NO2 7.291e-02 3.631e-03 20.08 <2e-16 ***
I(NO2^2) -8.731e-04 4.589e-05 -19.03 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 3751.1 on 64 degrees of freedom
Residual deviance: 2984.2 on 61 degrees of freedom
(31 observations deleted due to missingness)
AIC: 3507
Number of Fisher Scoring iterations: 4
Call:
glm(formula = J20 ~ NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.209e+00 4.991e-02 104.37 <2e-16 ***
NO2 4.310e-02 2.709e-03 15.91 <2e-16 ***
I(NO2^2) -4.900e-04 3.543e-05 -13.83 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 5425.2 on 93 degrees of freedom
Residual deviance: 5045.2 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 5788.6
Number of Fisher Scoring iterations: 4** El NO2 se asocia negativamente con el SO2. Por eso la asociación de la enfermedad J20 con el SO2 parece ser “negativa”. Es decir, la asociación negativa con el SO2 es muy posiblmente coincidental, y la asociación positiva con el NO2 es a la que es más prudente ponerele atención.
Column
NO2 - SO2
Modelo Unimodal: J:20 ~ NO2
Column
J:21 ~ SO2, NO2
Column
Enf. Respiratoria [J:21]
Predictor: SO2, NO2
Shapiro-Wilk normality test
data: m1$J21
W = 0.87589, p-value = 1.935e-07
Call:
glm(formula = J21 ~ SO2 + I(SO2^2) + NO2 + I(NO2^2), family = poisson,
data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.2168146 0.3071446 3.962 7.44e-05 ***
SO2 0.2313072 0.0221371 10.449 < 2e-16 ***
I(SO2^2) -0.0141242 0.0014384 -9.820 < 2e-16 ***
NO2 0.0671286 0.0155881 4.306 1.66e-05 ***
I(NO2^2) -0.0007123 0.0002003 -3.556 0.000377 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 920.86 on 64 degrees of freedom
Residual deviance: 795.95 on 60 degrees of freedom
(31 observations deleted due to missingness)
AIC: 1112.3
Number of Fisher Scoring iterations: 5
Call:
glm(formula = J21 ~ NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.5930615 0.2331330 6.833 8.30e-12 ***
NO2 0.0769173 0.0125110 6.148 7.85e-10 ***
I(NO2^2) -0.0008780 0.0001623 -5.411 6.28e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1228.3 on 93 degrees of freedom
Residual deviance: 1170.7 on 91 degrees of freedom
(2 observations deleted due to missingness)
AIC: 1613.9
Number of Fisher Scoring iterations: 5Column
Modelo Unimodal: J:21 ~ NO2
Column
Modelo Unimodal: J:21 ~ SO2
Column
Modelo Unimodal: J:21 ~ SO2
Enf.CP1[J0,J02,J03, J20] ~ AmbienteCP.1[Temperature]
Column
Componente.Princ 1 [J0,J02,J03, J20]
Predictor: AMB.CP1[Temprature]
Call:
glm(formula = enf.PC1 ~ amb.PCA.1, data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -9.830e-17 2.154e-01 0.000 1.000
amb.PCA.1 2.574e-01 1.330e-01 1.935 0.056 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 4.45605)
Null deviance: 435.56 on 95 degrees of freedom
Residual deviance: 418.87 on 94 degrees of freedom
AIC: 419.86
Number of Fisher Scoring iterations: 2El Amb.CP.1[Temperature] se asocia levemente con los puntajes del C.Pr-1_J[00,01, 02, 03, 20]. Esto no implica relación causal, pero sugiere asociación entre la temperatura ambiental (Tem. mínima y promedio) y algunas de las enfermedades J0, J01,J02, J03, J20.
Column
Modelo Unimodal: Componente 1 [J01, J04,J06,J:21,J:22] ~ PM2.5
Enf.CP.2[J01,J04,J06,J:21,J:22] ~ AmbienteCP.1[Temperature]
Column
Componente.Princ.2[J01,J04,J06,J:21,J:22]
Predictor: AMB.CP1[Temprature]
Call:
glm(formula = enf.PC2 ~ amb.PCA.1, data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.134e-17 1.125e-01 0.000 1.000
amb.PCA.1 7.524e-02 6.942e-02 1.084 0.281
(Dispersion parameter for gaussian family taken to be 1.214156)
Null deviance: 115.56 on 95 degrees of freedom
Residual deviance: 114.13 on 94 degrees of freedom
AIC: 295.04
Number of Fisher Scoring iterations: 2El Amb.CP.1[Temperature] No se asocia con los puntajes del C.Pr-2_J[J04,J06,J:21,J:22]. Esto sugiere asociación quizas entre la temperatura ambiental (Tem. mínima y promedio) y solo con algunas de las enfermedades.
Column
Modelo Unimodal: Componente.Princ.2[J01,J04,J06,J:21,J:22] ~ amb.PCA.1
Enfermedades ~ Ambiente.CP.2[Humedad, Precipit.Pluvial]
Column
Predictor: AMB.CP.2[Hum., Precip.Pluvial]
Componente.Princ 2 [J04,J06,J:21,J:22]
Call:
glm(formula = enf.PC2 ~ amb.PCA.2 + SO2 + I(SO2^2), data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.841206 0.242933 -3.463 0.000975 ***
amb.PCA.2 -0.239040 0.082105 -2.911 0.004994 **
SO2 0.372587 0.089563 4.160 9.97e-05 ***
I(SO2^2) -0.019330 0.005812 -3.326 0.001485 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 0.8720619)
Null deviance: 83.373 on 65 degrees of freedom
Residual deviance: 54.068 on 62 degrees of freedom
(30 observations deleted due to missingness)
AIC: 184.14
Number of Fisher Scoring iterations: 2El Amb.CP.2[Hum.Precip.Pluv] se asocia fuertemente con los puntajes del C.Pr-2_J[J04,J06,J:21,J:22]. Esto sugiere asociación entre la combinación de cantidad de lluvia & humedad y los niveles de SO2, con las enfermedades J21, J:22 y J:06.
Column
Column
Modelo: Componente 1 [J:00, J:01, J:02, J:03, J:20] ~ Amb.CP.2[Hum.Precip.Pluv]
Enf.CP1[J:00,J:02,J:03,J:20] ~ Ambiente, Contaminantes,etc
Column
Componente.Princ 1 [J:00,J:02,J:03,J:20]
Call:
glm(formula = enf.PC1 ~ cnrd.pca.1, data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.266e-16 2.196e-01 0.000 1.000
cnrd.pca.1 -7.058e-02 2.004e-01 -0.352 0.726
(Dispersion parameter for gaussian family taken to be 4.627479)
Null deviance: 435.56 on 95 degrees of freedom
Residual deviance: 434.98 on 94 degrees of freedom
AIC: 423.49
Number of Fisher Scoring iterations: 2Enfermedades y PM2.5
Column
Enfermedades y Ambiente
Column
CONRED [Componentes Principales]
***VECTORS
PC1 PC2 r2 Pr(>r)
con.masas -0.80006 0.59992 0.6989 0.001 ***
incendios -0.28550 -0.95838 0.1422 0.004 **
lluvias 0.89490 0.44627 0.2088 0.002 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Permutation: free
Number of permutations: 999
Call:
glm(formula = enf.PC1 ~ cnrd.pca.1 + cnrd.pca.2, data = m1)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.223e-16 2.207e-01 0.000 1.000
cnrd.pca.1 -7.058e-02 2.015e-01 -0.350 0.727
cnrd.pca.2 2.997e-02 2.083e-01 0.144 0.886
(Dispersion parameter for gaussian family taken to be 4.676196)
Null deviance: 435.56 on 95 degrees of freedom
Residual deviance: 434.89 on 93 degrees of freedom
AIC: 425.47
Number of Fisher Scoring iterations: 2Column
J0, J02 ~ Ambiente, Contaminantes,etc
Column
Shapiro-Wilk normality test
data: m1$J0
W = 0.98371, p-value = 0.2807
Call:
glm(formula = J0 ~ cnrd.pca.1 + cnrd.pca.2, family = poisson,
data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 8.194027 0.001697 4829.706 < 2e-16 ***
cnrd.pca.1 0.012247 0.001550 7.899 2.81e-15 ***
cnrd.pca.2 0.005088 0.001613 3.154 0.00161 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 23294 on 95 degrees of freedom
Residual deviance: 23221 on 93 degrees of freedom
AIC: 24187
Number of Fisher Scoring iterations: 4
Call:
glm(formula = J02 ~ cnrd.pca.1 + I(cnrd.pca.1^2) + cnrd.pca.2 +
I(cnrd.pca.2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 6.663599 0.005042 1321.62 <2e-16 ***
cnrd.pca.1 -0.074718 0.004671 -15.99 <2e-16 ***
I(cnrd.pca.1^2) 0.248648 0.010467 23.76 <2e-16 ***
cnrd.pca.2 -0.507054 0.020865 -24.30 <2e-16 ***
I(cnrd.pca.2^2) -0.265693 0.011326 -23.46 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 17224 on 95 degrees of freedom
Residual deviance: 16656 on 91 degrees of freedom
AIC: 17471
Number of Fisher Scoring iterations: 4Column
CONRED (conc.masas y lluvias)
CONRED (incendios)
Column
CONRED (conc.masas y lluvias)
CONRED (incendios)
J03 ~ Ambiente, Contaminantes,etc
Column
Call:
glm(formula = J03 ~ cnrd.pca.1 + I(cnrd.pca.1^2) + cnrd.pca.2 +
I(cnrd.pca.2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 7.465244 0.003382 2207.36 <2e-16 ***
cnrd.pca.1 -0.061130 0.003114 -19.63 <2e-16 ***
I(cnrd.pca.1^2) 0.248440 0.006984 35.58 <2e-16 ***
cnrd.pca.2 -0.504874 0.013906 -36.31 <2e-16 ***
I(cnrd.pca.2^2) -0.263204 0.007552 -34.85 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 24790 on 95 degrees of freedom
Residual deviance: 23581 on 91 degrees of freedom
AIC: 24478
Number of Fisher Scoring iterations: 4Column
CONRED (conc.masas y lluvias)
CONRED (incendios)
J06 ~ Ambiente, Contaminantes,etc
Column
J06
Call:
glm(formula = J06 ~ amb.PCA.1 + cnrd.pca.1 + I(cnrd.pca.1^2) +
cnrd.pca.2 + I(cnrd.pca.2^2) + PM2.5 + I(PM2.5^2) + NO2 +
I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.948e+00 5.764e-02 85.842 < 2e-16 ***
amb.PCA.1 9.091e-02 3.848e-03 23.622 < 2e-16 ***
cnrd.pca.1 -8.984e-02 6.678e-03 -13.454 < 2e-16 ***
I(cnrd.pca.1^2) 2.402e-01 1.354e-02 17.744 < 2e-16 ***
cnrd.pca.2 -4.777e-01 2.675e-02 -17.857 < 2e-16 ***
I(cnrd.pca.2^2) -2.697e-01 1.474e-02 -18.294 < 2e-16 ***
PM2.5 3.459e-02 1.738e-03 19.900 < 2e-16 ***
I(PM2.5^2) -3.522e-04 2.019e-05 -17.443 < 2e-16 ***
NO2 1.706e-02 2.847e-03 5.990 2.1e-09 ***
I(NO2^2) -1.028e-04 3.778e-05 -2.722 0.0065 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 9999.7 on 93 degrees of freedom
Residual deviance: 7835.6 on 84 degrees of freedom
(2 observations deleted due to missingness)
AIC: 8594.1
Number of Fisher Scoring iterations: 4
Column
Ambiente [Temperatura]
PM2.5
Column
CONRED (conc.masas y lluvias)
CONRED (incendios)
J20 ~ Ambiente, Contaminantes,etc
Column
J20
Call:
glm(formula = J20 ~ amb.PCA.1 + amb.PCA.2 + +PM2.5 + I(PM2.5^2) +
NO2 + I(NO2^2), family = poisson, data = m1)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.793e+00 5.799e-02 82.645 < 2e-16 ***
amb.PCA.1 4.106e-02 3.403e-03 12.067 < 2e-16 ***
amb.PCA.2 2.597e-02 3.840e-03 6.762 1.36e-11 ***
PM2.5 2.911e-02 1.756e-03 16.578 < 2e-16 ***
I(PM2.5^2) -2.733e-04 2.021e-05 -13.526 < 2e-16 ***
NO2 2.840e-02 2.845e-03 9.979 < 2e-16 ***
I(NO2^2) -2.747e-04 3.787e-05 -7.254 4.05e-13 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 5425.2 on 93 degrees of freedom
Residual deviance: 4476.4 on 87 degrees of freedom
(2 observations deleted due to missingness)
AIC: 5227.9
Number of Fisher Scoring iterations: 4
Column
AMB.PC.1 [Temperatura(-)]
AMB.CP.2[Precip.Pluvial-Hum.Relativa]
Column
PM2.5
NO2
Enf.PC1 ~ .
Column
enf.PCA1 [J0,J02,J03,J20]
Start: AIC=284.3
enf.PC1 ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2) + Temp.min + Rainfall +
Rel.Humidity
Df Deviance AIC
- Rel.Humidity 1 228.97 282.31
- PM2.5 1 232.50 283.30
- I(PM2.5^2) 1 233.31 283.53
- Rainfall 1 235.69 284.19
<none> 228.93 284.30
- Temp.min 1 248.83 287.72
- NO2 1 262.58 291.21
- I(NO2^2) 1 263.59 291.46
Step: AIC=282.31
enf.PC1 ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2) + Temp.min + Rainfall
Df Deviance AIC
- PM2.5 1 232.60 281.33
- I(PM2.5^2) 1 233.35 281.54
<none> 228.97 282.31
- Rainfall 1 240.83 283.59
+ Rel.Humidity 1 228.93 284.30
- Temp.min 1 248.97 285.75
- NO2 1 262.62 289.22
- I(NO2^2) 1 263.65 289.48
Step: AIC=281.33
enf.PC1 ~ I(PM2.5^2) + NO2 + I(NO2^2) + Temp.min + Rainfall
Df Deviance AIC
- I(PM2.5^2) 1 233.65 279.62
<none> 232.60 281.33
+ PM2.5 1 228.97 282.31
- Rainfall 1 243.66 282.35
+ Rel.Humidity 1 232.50 283.30
- Temp.min 1 255.70 285.49
- NO2 1 276.04 290.46
- I(NO2^2) 1 276.47 290.56
Step: AIC=279.62
enf.PC1 ~ NO2 + I(NO2^2) + Temp.min + Rainfall
Df Deviance AIC
<none> 233.65 279.62
- Rainfall 1 246.23 281.04
+ I(PM2.5^2) 1 232.60 281.33
+ PM2.5 1 233.35 281.54
+ Rel.Humidity 1 233.65 281.62
- Temp.min 1 257.00 283.82
- NO2 1 276.05 288.46
- I(NO2^2) 1 276.50 288.57
Call:
glm(formula = enf.PC1 ~ NO2 + I(NO2^2) + Temp.min + Rainfall,
data = m1.vars)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.004005 4.027751 0.001 0.99921
NO2 0.461819 0.139961 3.300 0.00163 **
I(NO2^2) -0.005979 0.001802 -3.317 0.00155 **
Temp.min -0.520074 0.212398 -2.449 0.01728 *
Rainfall 0.004596 0.002556 1.798 0.07726 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 3.894135)
Null deviance: 292.37 on 64 degrees of freedom
Residual deviance: 233.65 on 60 degrees of freedom
AIC: 279.62
Number of Fisher Scoring iterations: 2Column
Column
enf.PC1 ~ NO2 + I(NO2^2) + Temp.min + RainfallRecomiendo sacar Rainfall del modelo, debido a
que contribuye solo un 9 % a explicar el número de casos.
Call:
glm(formula = enf.PC1 ~ NO2 + I(NO2^2) + Temp.min, data = m1.vars)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.006101 3.939567 -0.509 0.61244
NO2 0.433898 0.141618 3.064 0.00325 **
I(NO2^2) -0.005626 0.001824 -3.085 0.00306 **
Temp.min -0.330934 0.187851 -1.762 0.08313 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 4.036595)
Null deviance: 292.37 on 64 degrees of freedom
Residual deviance: 246.23 on 61 degrees of freedom
AIC: 281.03
Number of Fisher Scoring iterations: 2J21 ~ .
Column
J21
Start: AIC=1201.46
J21 ~ NO2 + I(NO2^2) + PM2.5 + Rainfall + Rel.Humidity
Df Deviance AIC
- PM2.5 1 883.62 1200.0
- Rainfall 1 883.96 1200.3
<none> 883.12 1201.5
- NO2 1 892.10 1208.5
- I(NO2^2) 1 892.26 1208.6
- Rel.Humidity 1 896.29 1212.6
Step: AIC=1199.96
J21 ~ NO2 + I(NO2^2) + Rainfall + Rel.Humidity
Df Deviance AIC
- Rainfall 1 884.52 1198.9
<none> 883.62 1200.0
- NO2 1 893.90 1208.2
- I(NO2^2) 1 894.16 1208.5
- Rel.Humidity 1 899.18 1213.5
Step: AIC=1198.86
J21 ~ NO2 + I(NO2^2) + Rel.Humidity
Df Deviance AIC
<none> 884.52 1198.9
- NO2 1 894.93 1207.3
- I(NO2^2) 1 895.54 1207.9
- Rel.Humidity 1 907.42 1219.8
Call:
glm(formula = J21 ~ NO2 + I(NO2^2) + Rel.Humidity, family = "poisson",
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.2996066 0.5199626 8.269 < 2e-16 ***
NO2 0.0485994 0.0154659 3.142 0.00168 **
I(NO2^2) -0.0006381 0.0001979 -3.224 0.00126 **
Rel.Humidity -0.0260668 0.0054639 -4.771 1.84e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 920.86 on 64 degrees of freedom
Residual deviance: 884.52 on 61 degrees of freedom
AIC: 1198.9
Number of Fisher Scoring iterations: 5Column
Column
###
J22 ~ .
Column
J22
Call:
glm(formula = J22 ~ PM2.5 + I(PM2.5^2) + Temp.max + I(Temp.max^2) +
Rainfall + Rel.Humidity, family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.402e+01 1.055e+01 -1.329 0.18380
PM2.5 6.583e-02 1.131e-02 5.823 5.79e-09 ***
I(PM2.5^2) -6.183e-04 1.330e-04 -4.647 3.37e-06 ***
Temp.max 1.342e+00 8.212e-01 1.634 0.10228
I(Temp.max^2) -2.555e-02 1.590e-02 -1.606 0.10818
Rainfall 1.111e-03 4.006e-04 2.774 0.00554 **
Rel.Humidity -2.843e-02 1.158e-02 -2.455 0.01410 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1092.9 on 64 degrees of freedom
Residual deviance: 1003.4 on 58 degrees of freedom
AIC: 1302.5
Number of Fisher Scoring iterations: 5Column
Column
J06 ~ .
Column
J06
Call:
glm(formula = J06 ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) + Temp.min +
Rainfall + Rel.Humidity, family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.108e+00 1.822e-01 22.547 < 2e-16 ***
NO2 9.846e-02 3.981e-03 24.731 < 2e-16 ***
I(NO2^2) -1.114e-03 5.009e-05 -22.248 < 2e-16 ***
PM2.5 3.864e-02 2.474e-03 15.621 < 2e-16 ***
I(PM2.5^2) -4.460e-04 3.048e-05 -14.636 < 2e-16 ***
Temp.min -2.960e-02 4.963e-03 -5.964 2.46e-09 ***
Rainfall 1.144e-03 8.321e-05 13.753 < 2e-16 ***
Rel.Humidity -4.348e-03 1.920e-03 -2.264 0.0236 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 6338.2 on 64 degrees of freedom
Residual deviance: 4645.9 on 57 degrees of freedom
AIC: 5177.7
Number of Fisher Scoring iterations: 4Column
Column
3D - J06 ~ PM2.5 * NO2
Column
3D - J:06 ~ PM2.5 + (NO2)^2
Call:
glm(formula = J06 ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2) + PM2.5:NO2,
family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.551e+00 1.245e-01 28.518 <2e-16 ***
PM2.5 3.752e-02 3.474e-03 10.799 <2e-16 ***
I(PM2.5^2) -4.277e-04 3.072e-05 -13.921 <2e-16 ***
NO2 9.688e-02 5.179e-03 18.708 <2e-16 ***
I(NO2^2) -1.087e-03 5.159e-05 -21.077 <2e-16 ***
PM2.5:NO2 -6.436e-05 6.768e-05 -0.951 0.342
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 6338.2 on 64 degrees of freedom
Residual deviance: 4957.9 on 59 degrees of freedom
AIC: 5485.8
Number of Fisher Scoring iterations: 4Column
J01 ~ .
Column
J01
Call:
glm(formula = J01 ~ NO2 + I(NO2^2) + Temp.min + Rainfall, family = "poisson",
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.7330424 0.3619455 10.314 < 2e-16 ***
NO2 0.0501492 0.0134074 3.740 0.000184 ***
I(NO2^2) -0.0007434 0.0001746 -4.258 2.06e-05 ***
Temp.min -0.0609682 0.0184989 -3.296 0.000981 ***
Rainfall -0.0005102 0.0002361 -2.161 0.030691 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 458.28 on 64 degrees of freedom
Residual deviance: 413.60 on 60 degrees of freedom
AIC: 762.82
Number of Fisher Scoring iterations: 5Column
Column
J04 ~ .
Column
J04
Start: AIC=658.44
J04 ~ NO2 + I(NO2^2)
Df Deviance AIC
<none> 303.62 658.44
- NO2 1 315.88 668.70
- I(NO2^2) 1 317.68 670.50
Call:
glm(formula = J04 ~ NO2 + I(NO2^2), family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.8760684 0.2351118 12.233 < 2e-16 ***
NO2 0.0427341 0.0125017 3.418 0.000630 ***
I(NO2^2) -0.0005863 0.0001608 -3.647 0.000265 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 319.02 on 64 degrees of freedom
Residual deviance: 303.62 on 62 degrees of freedom
AIC: 658.44
Number of Fisher Scoring iterations: 4Column
J0 ~ .
Column
J0
Start: AIC=11244.8
J0 ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) + Temp.min + Rainfall +
Rel.Humidity
Df Deviance AIC
<none> 10575 11245
- Rel.Humidity 1 10662 11330
- PM2.5 1 10714 11382
- I(PM2.5^2) 1 10748 11417
- Rainfall 1 11157 11826
- Temp.min 1 11555 12224
- NO2 1 11866 12535
- I(NO2^2) 1 11984 12652
Call:
glm(formula = J0 ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) + Temp.min +
Rainfall + Rel.Humidity, family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 8.586e+00 6.406e-02 134.033 <2e-16 ***
NO2 4.531e-02 1.286e-03 35.221 <2e-16 ***
I(NO2^2) -6.080e-04 1.654e-05 -36.767 <2e-16 ***
PM2.5 9.685e-03 8.264e-04 11.720 <2e-16 ***
I(PM2.5^2) -1.323e-04 1.016e-05 -13.023 <2e-16 ***
Temp.min -5.513e-02 1.758e-03 -31.355 <2e-16 ***
Rainfall 7.198e-04 2.972e-05 24.216 <2e-16 ***
Rel.Humidity -6.342e-03 6.792e-04 -9.338 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 13299 on 64 degrees of freedom
Residual deviance: 10575 on 57 degrees of freedom
AIC: 11245
Number of Fisher Scoring iterations: 4Column
Column
3D – J0 ~ PM2.5 * NO2 * Temp.min
Column
J0 ~ PM2.5 * NO2 * Temp.min
Call:
glm(formula = J0 ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2) + Temp.min +
+PM2.5:NO2 + NO2:Temp.min, family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 9.898e+00 1.289e-01 76.783 < 2e-16 ***
PM2.5 -4.059e-03 1.231e-03 -3.298 0.000973 ***
I(PM2.5^2) -9.785e-05 1.050e-05 -9.321 < 2e-16 ***
NO2 -1.424e-02 3.742e-03 -3.805 0.000142 ***
I(NO2^2) -4.138e-04 1.942e-05 -21.311 < 2e-16 ***
Temp.min -1.218e-01 6.232e-03 -19.551 < 2e-16 ***
PM2.5:NO2 2.976e-04 2.402e-05 12.387 < 2e-16 ***
NO2:Temp.min 2.260e-03 1.564e-04 14.452 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 13299 on 64 degrees of freedom
Residual deviance: 11004 on 57 degrees of freedom
AIC: 11674
Number of Fisher Scoring iterations: 4J30 ~ PM2.5 * NO2
Call:
glm(formula = J0 ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2) + PM2.5:NO2,
family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 7.479e+00 3.879e-02 192.797 < 2e-16 ***
PM2.5 9.223e-03 1.106e-03 8.337 < 2e-16 ***
I(PM2.5^2) -1.665e-04 1.010e-05 -16.478 < 2e-16 ***
NO2 3.433e-02 1.683e-03 20.390 < 2e-16 ***
I(NO2^2) -4.859e-04 1.706e-05 -28.480 < 2e-16 ***
PM2.5:NO2 9.381e-05 2.259e-05 4.152 3.29e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 13299 on 64 degrees of freedom
Residual deviance: 11706 on 59 degrees of freedom
AIC: 12372
Number of Fisher Scoring iterations: 4Column
3D – J0 ~ PM2.5 * Temp.min
Column
J0 ~ PM2.5 * Temp.min
Call:
glm(formula = J0 ~ PM2.5 + I(PM2.5^2) + Temp.min + PM2.5:Temp.min,
family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 7.576e+00 7.418e-02 102.131 < 2e-16 ***
PM2.5 3.484e-02 2.206e-03 15.793 < 2e-16 ***
I(PM2.5^2) -1.935e-04 1.008e-05 -19.206 < 2e-16 ***
Temp.min 2.343e-02 4.426e-03 5.293 1.21e-07 ***
PM2.5:Temp.min -1.169e-03 1.276e-04 -9.163 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 13299 on 64 degrees of freedom
Residual deviance: 12564 on 60 degrees of freedom
AIC: 13228
Number of Fisher Scoring iterations: 4Column
3D – J0 ~ NO2 * Temp.min
Column
J0 ~ NO2 * Temp.min
Call:
glm(formula = J0 ~ NO2 + I(NO2^2) + Temp.min + NO2:Temp.min,
family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 9.0630952 0.0971546 93.285 < 2e-16 ***
NO2 0.0141499 0.0030032 4.712 2.46e-06 ***
I(NO2^2) -0.0005173 0.0000175 -29.566 < 2e-16 ***
Temp.min -0.0934084 0.0054267 -17.213 < 2e-16 ***
NO2:Temp.min 0.0015665 0.0001402 11.171 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 13299 on 64 degrees of freedom
Residual deviance: 11351 on 60 degrees of freedom
AIC: 12015
Number of Fisher Scoring iterations: 4Column
NO2 & SO2 ~ Temperature.
Column
NO2 ~ Temp.min
Start: AIC=486.83
NO2 ~ Temp.min + Temp.max + Rainfall + Rel.Humidity
Df Deviance AIC
- Rel.Humidity 1 5663.3 484.84
- Rainfall 1 5681.6 485.05
- Temp.max 1 5702.4 485.29
<none> 5662.0 486.83
- Temp.min 1 5991.7 488.51
Step: AIC=484.84
NO2 ~ Temp.min + Temp.max + Rainfall
Df Deviance AIC
- Rainfall 1 5687.8 483.12
- Temp.max 1 5744.6 483.77
<none> 5663.3 484.84
- Temp.min 1 6001.5 486.61
+ Rel.Humidity 1 5662.0 486.83
Step: AIC=483.12
NO2 ~ Temp.min + Temp.max
Df Deviance AIC
- Temp.max 1 5747.6 481.80
<none> 5687.8 483.12
+ Rainfall 1 5663.3 484.84
+ Rel.Humidity 1 5681.6 485.05
- Temp.min 1 6422.6 489.02
Step: AIC=481.8
NO2 ~ Temp.min
Df Deviance AIC
<none> 5747.6 481.80
+ Temp.max 1 5687.8 483.12
+ Rel.Humidity 1 5736.5 483.68
+ Rainfall 1 5744.6 483.77
- Temp.min 1 6889.9 491.58
Call:
glm(formula = NO2 ~ Temp.min, data = m1.vars)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 82.5151 12.7848 6.454 1.77e-08 ***
Temp.min -2.8303 0.7998 -3.539 0.000762 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 91.23111)
Null deviance: 6889.9 on 64 degrees of freedom
Residual deviance: 5747.6 on 63 degrees of freedom
AIC: 481.8
Number of Fisher Scoring iterations: 2Column
Column
SO2 ~ Temp.max
Start: AIC=373.23
SO2 ~ Temp.max + Temp.min + Rainfall + Rel.Humidity
Df Deviance AIC
- Temp.min 1 989.67 371.46
- Rel.Humidity 1 992.44 371.64
- Rainfall 1 1002.43 372.29
<none> 986.25 373.23
- Temp.max 1 1060.35 375.94
Step: AIC=371.46
SO2 ~ Temp.max + Rainfall + Rel.Humidity
Df Deviance AIC
- Rel.Humidity 1 998.62 370.04
- Rainfall 1 1002.96 370.32
<none> 989.67 371.46
+ Temp.min 1 986.25 373.23
- Temp.max 1 1124.96 377.78
Step: AIC=370.04
SO2 ~ Temp.max + Rainfall
Df Deviance AIC
- Rainfall 1 1002.99 368.33
<none> 998.62 370.04
+ Rel.Humidity 1 989.67 371.46
+ Temp.min 1 992.44 371.64
- Temp.max 1 1152.09 377.33
Step: AIC=368.33
SO2 ~ Temp.max
Df Deviance AIC
<none> 1002.99 368.33
+ Rainfall 1 998.62 370.04
+ Temp.min 1 1002.52 370.29
+ Rel.Humidity 1 1002.96 370.32
- Temp.max 1 1159.93 375.77
Call:
glm(formula = SO2 ~ Temp.max, data = m1.vars)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -27.9182 10.3854 -2.688 0.00918 **
Temp.max 1.2548 0.3996 3.140 0.00257 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 15.92049)
Null deviance: 1159.9 on 64 degrees of freedom
Residual deviance: 1003.0 on 63 degrees of freedom
AIC: 368.33
Number of Fisher Scoring iterations: 2Column
SO2 ~ Temperature
NO2 & PM2.5 ~ Temperature.
Column
NO2 ~ PM2.5
Start: AIC=492.9
NO2 ~ PM2.5 + I(PM2.5^2)
Df Deviance AIC
<none> 6611.0 492.90
- PM2.5 1 6856.7 493.27
- I(PM2.5^2) 1 6886.6 493.55
Call:
glm(formula = NO2 ~ PM2.5 + I(PM2.5^2), data = m1.vars)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25.052187 9.101634 2.752 0.00775 **
PM2.5 0.724517 0.477293 1.518 0.13410
I(PM2.5^2) -0.009510 0.005916 -1.608 0.11301
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 106.6296)
Null deviance: 6889.9 on 64 degrees of freedom
Residual deviance: 6611.0 on 62 degrees of freedom
AIC: 492.9
Number of Fisher Scoring iterations: 2Column
Column
SO2 ~ Temp.max
Start: AIC=373.23
SO2 ~ Temp.max + Temp.min + Rainfall + Rel.Humidity
Df Deviance AIC
- Temp.min 1 989.67 371.46
- Rel.Humidity 1 992.44 371.64
- Rainfall 1 1002.43 372.29
<none> 986.25 373.23
- Temp.max 1 1060.35 375.94
Step: AIC=371.46
SO2 ~ Temp.max + Rainfall + Rel.Humidity
Df Deviance AIC
- Rel.Humidity 1 998.62 370.04
- Rainfall 1 1002.96 370.32
<none> 989.67 371.46
+ Temp.min 1 986.25 373.23
- Temp.max 1 1124.96 377.78
Step: AIC=370.04
SO2 ~ Temp.max + Rainfall
Df Deviance AIC
- Rainfall 1 1002.99 368.33
<none> 998.62 370.04
+ Rel.Humidity 1 989.67 371.46
+ Temp.min 1 992.44 371.64
- Temp.max 1 1152.09 377.33
Step: AIC=368.33
SO2 ~ Temp.max
Df Deviance AIC
<none> 1002.99 368.33
+ Rainfall 1 998.62 370.04
+ Temp.min 1 1002.52 370.29
+ Rel.Humidity 1 1002.96 370.32
- Temp.max 1 1159.93 375.77
Call:
glm(formula = SO2 ~ Temp.max, data = m1.vars)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -27.9182 10.3854 -2.688 0.00918 **
Temp.max 1.2548 0.3996 3.140 0.00257 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for gaussian family taken to be 15.92049)
Null deviance: 1159.9 on 64 degrees of freedom
Residual deviance: 1003.0 on 63 degrees of freedom
AIC: 368.33
Number of Fisher Scoring iterations: 2Chronic Diseases: J30 ~ .
Column
J30
Start: AIC=1454.97
`J:30` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) + Temp.min + Rainfall +
Rel.Humidity
Df Deviance AIC
<none> 972.30 1455.0
- PM2.5 1 986.16 1466.8
- I(PM2.5^2) 1 986.54 1467.2
- Rel.Humidity 1 987.56 1468.2
- Rainfall 1 1074.13 1554.8
- I(NO2^2) 1 1108.53 1589.2
- Temp.min 1 1122.99 1603.7
- NO2 1 1129.09 1609.8
Call:
glm(formula = `J:30` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) +
Temp.min + Rainfall + Rel.Humidity, family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.371e+00 2.930e-01 18.331 < 2e-16 ***
NO2 8.648e-02 7.150e-03 12.095 < 2e-16 ***
I(NO2^2) -9.924e-04 8.787e-05 -11.294 < 2e-16 ***
PM2.5 1.956e-02 5.305e-03 3.688 0.000226 ***
I(PM2.5^2) -2.341e-04 6.283e-05 -3.726 0.000195 ***
Temp.min -8.906e-02 7.254e-03 -12.277 < 2e-16 ***
Rainfall 1.299e-03 1.280e-04 10.145 < 2e-16 ***
Rel.Humidity -1.170e-02 2.992e-03 -3.912 9.15e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1316.3 on 64 degrees of freedom
Residual deviance: 972.3 on 57 degrees of freedom
AIC: 1455
Number of Fisher Scoring iterations: 4Column
Column
3D – J30 ~ PM2.5 * NO2 * Temp.min
Column
J30 ~ PM2.5 * NO2 * Temp.min
Call:
glm(formula = `J:30` ~ I(PM2.5^2) + I(NO2^2) + Temp.min + PM2.5:NO2 +
PM2.5:Temp.min + NO2:Temp.min, family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 6.403e+00 1.877e-01 34.119 < 2e-16 ***
I(PM2.5^2) -2.255e-04 6.687e-05 -3.373 0.000744 ***
I(NO2^2) -6.674e-04 6.527e-05 -10.224 < 2e-16 ***
Temp.min -9.597e-02 2.038e-02 -4.708 2.50e-06 ***
PM2.5:NO2 8.119e-04 1.128e-04 7.199 6.05e-13 ***
Temp.min:PM2.5 -8.886e-04 3.124e-04 -2.845 0.004446 **
Temp.min:NO2 2.037e-03 3.782e-04 5.385 7.24e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1316.3 on 64 degrees of freedom
Residual deviance: 1045.9 on 58 degrees of freedom
AIC: 1526.6
Number of Fisher Scoring iterations: 4J30 ~ PM2.5 * NO2
Call:
glm(formula = `J:30` ~ I(PM2.5^2) + NO2 + I(NO2^2) + PM2.5:NO2,
family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.401e+00 1.550e-01 28.392 < 2e-16 ***
I(PM2.5^2) -3.395e-04 5.313e-05 -6.390 1.66e-10 ***
NO2 4.082e-02 8.166e-03 4.999 5.76e-07 ***
I(NO2^2) -7.044e-04 8.583e-05 -8.207 2.26e-16 ***
NO2:PM2.5 7.045e-04 1.129e-04 6.242 4.32e-10 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1316.3 on 64 degrees of freedom
Residual deviance: 1118.3 on 60 degrees of freedom
AIC: 1595
Number of Fisher Scoring iterations: 4Column
3D – J30 ~ PM2.5 * Temp.min
Column
J30 ~ PM2.5 * Temp.min
Call:
glm(formula = `J:30` ~ PM2.5 + Temp.min + PM2.5:Temp.min, family = poisson,
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.2033949 0.3539846 14.699 < 2e-16 ***
PM2.5 0.0273460 0.0093828 2.914 0.00356 **
Temp.min 0.0094538 0.0219371 0.431 0.66650
PM2.5:Temp.min -0.0016676 0.0005824 -2.864 0.00419 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1316.3 on 64 degrees of freedom
Residual deviance: 1223.8 on 61 degrees of freedom
AIC: 1698.5
Number of Fisher Scoring iterations: 4Column
3D – J30 ~ NO2 * Temp.min
Column
J30 ~ NO2 * Temp.min
Call:
glm(formula = `J:30` ~ NO2 + I(NO2^2) + Temp.min + NO2:Temp.min,
family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.705e+00 4.403e-01 12.958 < 2e-16 ***
NO2 4.176e-02 1.316e-02 3.174 0.0015 **
I(NO2^2) -7.403e-04 8.702e-05 -8.507 < 2e-16 ***
Temp.min -1.082e-01 2.514e-02 -4.304 1.68e-05 ***
NO2:Temp.min 1.552e-03 6.249e-04 2.484 0.0130 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1316.3 on 64 degrees of freedom
Residual deviance: 1092.0 on 60 degrees of freedom
AIC: 1568.6
Number of Fisher Scoring iterations: 4Column
J32 ~ .
Column
J32
Start: AIC=482.81
`J:32` ~ NO2 + I(NO2^2) + Temp.min
Df Deviance AIC
<none> 193.85 482.81
- NO2 1 203.51 490.47
- I(NO2^2) 1 206.06 493.02
- Temp.min 1 235.47 522.43
Call:
glm(formula = `J:32` ~ NO2 + I(NO2^2) + Temp.min, family = "poisson",
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.6693935 0.6226804 5.893 3.79e-09 ***
NO2 0.0830049 0.0277077 2.996 0.002738 **
I(NO2^2) -0.0011797 0.0003528 -3.343 0.000827 ***
Temp.min -0.1530024 0.0234398 -6.527 6.69e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 241.40 on 64 degrees of freedom
Residual deviance: 193.85 on 61 degrees of freedom
AIC: 482.81
Number of Fisher Scoring iterations: 4Column
Column
J44 ~ .
Column
J44
Start: AIC=389.38
`J:44` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2)
Df Deviance AIC
<none> 126.28 389.38
- I(NO2^2) 1 129.27 390.38
- NO2 1 129.93 391.03
- I(PM2.5^2) 1 137.68 398.79
- PM2.5 1 138.10 399.21
Call:
glm(formula = `J:44` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2), family = "poisson",
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.1252930 0.9128206 -1.233 0.21766
NO2 0.0643187 0.0345842 1.860 0.06292 .
I(NO2^2) -0.0007178 0.0004256 -1.687 0.09170 .
PM2.5 0.0970765 0.0299911 3.237 0.00121 **
I(PM2.5^2) -0.0011389 0.0003625 -3.142 0.00168 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 142.87 on 64 degrees of freedom
Residual deviance: 126.28 on 60 degrees of freedom
AIC: 389.38
Number of Fisher Scoring iterations: 5Column
Column ———— ###
3D – J44 ~ PM2.5 * NO2
Column
J44 ~ PM2.5 * NO2
Call:
glm(formula = `J:44` ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2), family = poisson,
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.1252930 0.9128206 -1.233 0.21766
PM2.5 0.0970765 0.0299911 3.237 0.00121 **
I(PM2.5^2) -0.0011389 0.0003625 -3.142 0.00168 **
NO2 0.0643187 0.0345842 1.860 0.06292 .
I(NO2^2) -0.0007178 0.0004256 -1.687 0.09170 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 142.87 on 64 degrees of freedom
Residual deviance: 126.28 on 60 degrees of freedom
AIC: 389.38
Number of Fisher Scoring iterations: 5Column
J45 ~ .
Column
J45
Start: AIC=2705.25
`J:45` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) + Temp.min
Df Deviance AIC
<none> 2212.3 2705.2
- PM2.5 1 2215.8 2706.8
- I(PM2.5^2) 1 2221.6 2712.6
- Temp.min 1 2399.1 2890.1
- NO2 1 2431.7 2922.7
- I(NO2^2) 1 2442.6 2933.5
Call:
glm(formula = `J:45` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2) +
Temp.min, family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.055e+00 1.800e-01 28.079 < 2e-16 ***
NO2 8.981e-02 6.296e-03 14.264 < 2e-16 ***
I(NO2^2) -1.152e-03 7.910e-05 -14.561 < 2e-16 ***
PM2.5 9.003e-03 4.813e-03 1.871 0.06140 .
I(PM2.5^2) -1.755e-04 5.796e-05 -3.028 0.00246 **
Temp.min -7.336e-02 5.337e-03 -13.744 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 2617.3 on 64 degrees of freedom
Residual deviance: 2212.3 on 59 degrees of freedom
AIC: 2705.2
Number of Fisher Scoring iterations: 4Column
Column
Not_Specified Diseases: J18 ~ .
Column
J18
Start: AIC=3598.61
`J:18` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2)
Call:
glm(formula = `J:18` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2), family = "poisson",
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.288e+00 1.154e-01 28.49 <2e-16 ***
NO2 5.819e-02 5.776e-03 10.07 <2e-16 ***
I(NO2^2) -7.396e-04 7.331e-05 -10.09 <2e-16 ***
PM2.5 5.875e-02 4.209e-03 13.96 <2e-16 ***
I(PM2.5^2) -8.164e-04 5.545e-05 -14.72 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 3597.6 on 64 degrees of freedom
Residual deviance: 3132.2 on 60 degrees of freedom
AIC: 3598.6
Number of Fisher Scoring iterations: 4Column
Column
3D – J18 ~ PM2.5 * NO2
Column
J18 ~ PM2.5 * NO2
Call:
glm(formula = `J:18` ~ PM2.5 + I(PM2.5^2) + NO2 + I(NO2^2) +
PM2.5:NO2, family = poisson, data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.474e+00 1.880e-01 13.163 < 2e-16 ***
PM2.5 7.850e-02 5.486e-03 14.311 < 2e-16 ***
I(PM2.5^2) -8.106e-04 5.501e-05 -14.736 < 2e-16 ***
NO2 8.779e-02 7.873e-03 11.151 < 2e-16 ***
I(NO2^2) -8.871e-04 7.775e-05 -11.410 < 2e-16 ***
PM2.5:NO2 -5.926e-04 1.048e-04 -5.653 1.58e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 3597.6 on 64 degrees of freedom
Residual deviance: 3100.1 on 59 degrees of freedom
AIC: 3568.4
Number of Fisher Scoring iterations: 4Column
J98 ~ .
Column
J98
Start: AIC=541.26
`J:98` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2)
Call:
glm(formula = `J:98` ~ NO2 + I(NO2^2) + PM2.5 + I(PM2.5^2), family = "poisson",
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.4168071 0.3553203 3.987 6.68e-05 ***
NO2 0.0597128 0.0182508 3.272 0.001069 **
I(NO2^2) -0.0008196 0.0002347 -3.492 0.000479 ***
PM2.5 0.0313581 0.0115102 2.724 0.006442 **
I(PM2.5^2) -0.0003758 0.0001434 -2.621 0.008777 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 249.11 on 64 degrees of freedom
Residual deviance: 221.72 on 60 degrees of freedom
AIC: 541.26
Number of Fisher Scoring iterations: 4Column
Column
3D – J98 ~ PM2.5 * NO2
Column
Call:
glm(formula = `J:98` ~ I(PM2.5^2) + I(NO2^2) + PM2.5:NO2, family = poisson,
data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.919e+00 7.811e-02 37.365 < 2e-16 ***
I(PM2.5^2) -3.927e-04 8.843e-05 -4.441 8.96e-06 ***
I(NO2^2) -4.421e-04 8.664e-05 -5.102 3.35e-07 ***
PM2.5:NO2 9.856e-04 1.884e-04 5.230 1.69e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 249.11 on 64 degrees of freedom
Residual deviance: 216.70 on 61 degrees of freedom
AIC: 534.25
Number of Fisher Scoring iterations: 4Column
J40 ~ .
Column
J40
Start: AIC=492.92
`J:40` ~ NO2 + PM2.5 + Temp.avg
Df Deviance AIC
- PM2.5 1 220.07 491.30
- Temp.avg 1 220.42 491.65
<none> 219.69 492.92
- NO2 1 222.19 493.43
Step: AIC=491.3
`J:40` ~ NO2 + Temp.avg
Df Deviance AIC
- Temp.avg 1 220.66 489.89
<none> 220.07 491.30
- NO2 1 222.51 491.74
+ PM2.5 1 219.69 492.92
Step: AIC=489.89
`J:40` ~ NO2
Df Deviance AIC
- NO2 1 222.56 489.79
<none> 220.66 489.89
+ Temp.avg 1 220.07 491.30
+ PM2.5 1 220.42 491.65
Step: AIC=489.79
`J:40` ~ 1
Df Deviance AIC
<none> 222.56 489.79
+ NO2 1 220.66 489.89
+ PM2.5 1 222.29 491.53
+ Temp.avg 1 222.51 491.74
Call:
glm(formula = `J:40` ~ 1, family = "poisson", data = m1.vars)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.39088 0.03753 63.71 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 222.56 on 64 degrees of freedom
Residual deviance: 222.56 on 64 degrees of freedom
AIC: 489.79
Number of Fisher Scoring iterations: 5Column
Column
