Librerías Implementadas

library(raster)
library(tiff)
library(ggplot2)
library(forecast)

Condiciones Necesarias

n=16 # numero de mapas de Covid19
Representante<- matrix(nrow = n, ncol = 1)
Semana <- matrix(nrow = n, ncol = 1)

Lectura de Imágenes y ejecución de la descomposición

for(k in 1:n){
concat <- gsub(' ','',paste(k,'.tif'))
direc <- file.path('C:/Users/Fabian Navarro/Google Drive/Proyecto_Covid19DMD/mapas',concat)
mapa_matriz <- readTIFF(direc)
dimen<- dim(mapa_matriz)

for(j in 1:dimen[1]){
  for(i in 1:dimen[2]){
    if(mapa_matriz[i,j]<(-1)){
      mapa_matriz[i,j]=0
    }
  }
}

Des_svd <- svd(mapa_matriz)

Representante[k,1]<- Des_svd$d[1] 
Semana[k,1]<- paste('Semana',k)
}

Serie de Tiempo

DB <- data.frame(Semana,Representante)
Representantes <- ts(DB$Representante, frequency = 2)
plot(Representantes, xlab= "Semanas", main= "COVID19")

Comportamiento \(ARMA(p,q)\)

auto.arima(Representantes)
## Series: Representantes 
## ARIMA(0,0,0)(1,0,0)[2] with non-zero mean 
## 
## Coefficients:
##          sar1     mean
##       -0.5469  61.8728
## s.e.   0.2618   4.2920
## 
## sigma^2 estimated as 731.6:  log likelihood=-74.75
## AIC=155.5   AICc=157.5   BIC=157.82

Descomposición de la serie de tiempo

var<- stl(Representantes, s.window="periodic", robust = TRUE)
plot(var)

Modelo Lineal Polinomial de Orden 3

modelo3<-lm(Representantes~time(Representantes)+I(time(Representantes)^2)+I(time(Representantes)^3))
summary(modelo3)#mod.cub #original
## 
## Call:
## lm(formula = Representantes ~ time(Representantes) + I(time(Representantes)^2) + 
##     I(time(Representantes)^3))
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -37.408 -14.805  -2.118   9.191  53.841 
## 
## Coefficients:
##                           Estimate Std. Error t value Pr(>|t|)
## (Intercept)               -36.7563    53.2156  -0.691    0.503
## time(Representantes)       66.6097    44.0420   1.512    0.156
## I(time(Representantes)^2) -13.9456    10.3356  -1.349    0.202
## I(time(Representantes)^3)   0.9303     0.7183   1.295    0.220
## 
## Residual standard error: 27.04 on 12 degrees of freedom
## Multiple R-squared:  0.3341, Adjusted R-squared:  0.1676 
## F-statistic: 2.007 on 3 and 12 DF,  p-value: 0.1668