layerNames(s_raster_r)<-tab_range$varterm[k]

    val_rst[[k]]<-s_raster_r

  }

  ###Regression part 1: Creating a validation dataset by creating training and testing datasets

  mod_LST <-ghcn.subsets[[i]][,match(LST_month, names(ghcn.subsets[[i]]))]  #Match interpolation date and monthly LST average

  #n<-nrow(ghcn.subsets[[i]])

  #ns<-n-round(n*prop)   #Create a sample from the data frame with 70% of the rows

  #nv<-n-ns              #create a sample for validation with prop of the rows

  formula5 <- as.formula("y_var~ lat + lon + ELEV_SRTM + Northness_w + Eastness_w + DISTOC + LST", env=.GlobalEnv)

  formula6 <- as.formula("y_var~ lat + lon + ELEV_SRTM + Northness_w + Eastness_w + DISTOC + LST + LC1", env=.GlobalEnv)

  formula7 <- as.formula("y_var~ lat + lon + ELEV_SRTM + Northness_w + Eastness_w + DISTOC + LST + LC3", env=.GlobalEnv)

  #   bwG <- gwr.sel(tmax~ lon + lat + ELEV_SRTM + Eastness + Northness + DISTOC,data=data_s,gweight=gwr.Gauss, verbose = FALSE)

  #   gwrG<- gwr(tmax~ lon + lat + ELEV_SRTM + Eastness + Northness + DISTOC, data=data_s, bandwidth=bwG, gweight=gwr.Gauss, hatmatrix=TRUE)

      mod_varn<-t_l

    }

    #browser()

    list_rst<-vector("list",length(mod_varn))

    pos<-match(mod_varn,layerNames(s_rst_m)) #Find column with the current month for instance mm12 

    s_rst_mod<-subset(s_rst_m,pos)

    coordinates(s_spdf)<-coords

    proj4string(s_spdf)<-CRS  #Need to assign coordinates...

    #If mod "j" is not a model object

    if (inherits(mod,"try-error")) {

    #If mod "j" is not a model object

    if (inherits(mod,"gwr")) {

      pred_gwr[[j]]<-pred   #prediction stored in a list