R help - Sep 2020 - calculating a linear regression for each grid cell. firstly

Hi all,


            for example, ? have 4 raster data and ? try to convert these rasters
to 1 array and calculate a linear regression for each grid cell how can ? do
this?



                max_consecutive_days_1<- raster(ncol=94, nrow=192, xmn=-180,
xmx=180, ymn=-90, ymx=90)
                max_consecutive_days_2<- raster(ncol=94, nrow=192, xmn=-180,
xmx=180, ymn=-90, ymx=90)
                max_consecutive_days_3<- raster(ncol=94, nrow=192, xmn=-180,
xmx=180, ymn=-90, ymx=90)
                max_consecutive_days_4<- raster(ncol=94, nrow=192, xmn=-180,
xmx=180, ymn=-90, ymx=90)

                values(max_consecutive_days_1)  <-
1:ncell(max_consecutive_days_1)
                values(max_consecutive_days_2) <-
1:ncell(max_consecutive_days_2)
                values(max_consecutive_days_3) <-
1:ncell(max_consecutive_days_3)
                values(max_consecutive_days_4) <-
1:ncell(max_consecutive_days_4)
                set.seed(0)
                values(max_consecutive_days_1)  <-
runif(ncell(max_consecutive_days_1))
                values(max_consecutive_days_2) <-
runif(ncell(max_consecutive_days_2))
                values(max_consecutive_days_3) <-
runif(ncell(max_consecutive_days_3))
                values(max_consecutive_days_4) <-
runif(ncell(max_consecutive_days_4))

         I tried to convert raster to an array and calculate a linear regression
for each cell with these codes. there is something wrong in codes but I
didn't find what it's wrong

        library(raster)
            r<-raster("C:/max_consecutive_days_1.tif")
            a<-array(NA,dim=c(dim(r)[1:2],4))
            i <- 1
            dir.in <- "C:/max_consecutive_days/"
            for (year in 1:4) {
             
fi<-paste0(dir.in,"max_consecutive_days_",year,".tif")
              r<-raster(fi)
              a[,,i]<-getValues(r,format="matrix")
              i<-i+1
            }


     lmfunction <- function(x){

              if (is.na(x[1])){ NA }

              else

                y<-c(1:length(x))
              m1<- summary(lm(x~y))
              coef <- m1$coef[2]

              coef
             }

            storem <- array(NA,dim=dim(a)[1:2])
            for(i in 1:94){
              for(j in 1:192){
                tst<-mean(a[i,j,],n.rm=T)
                if (is.na(tst)==F){
                  storem[i,j]<-lmfunction(a[i,j,])
                }
              }
            }


Best wishes,

Windows 10 i?in Posta<https://go.microsoft.com/fwlink/?LinkId=550986> ile
g?nderildi


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