gistfile1.txt

registerDoParallel(cores=8)
set.seed(123)
Eggs2<-day%>%
  filter(location_identification==1)%>%
  mutate(egg_count = zoo::na.aggregate(egg_count),
         feed_provided = zoo::na.aggregate(feed_provided),
         water_provided = zoo::na.aggregate(water_provided),
         animals_actual = zoo::na.aggregate(animals_actual),
         t_min_out = zoo::na.aggregate(t_min_out),
         t_max_out = zoo::na.aggregate(t_min_out),
         t_act_out = zoo::na.aggregate(t_min_out),
         rh_act_in = zoo::na.spline(rh_act_in))%>%
  dplyr::select(egg_count,
                date_interval,
                water_provided,
                feed_provided,
                animals_actual,
                t_min_out,
                t_max_out,
                t_act_out,
                rh_act_in)
myTimeControl <- trainControl(method = "timeslice",
                              initialWindow = 50,
                              horizon = 7,
                              fixedWindow = FALSE,
                              allowParallel = TRUE)
model_names <- c("glmnet", "lm",
                 "earth", "gam", "rpart",
                 "ctree", "gbm", "rf")
fits<-map(model_names,
            ~ train(
              egg_count ~ . - 1,
              data = Eggs2,
              method = .x,
              trControl = myTimeControl,
              na.action=na.omit
            ))%>%
  set_names(model_names)
resamps <- resamples(fits)
ss <- summary(resamps)
ss[[3]]$RMSE
trellis.par.set(caretTheme())
dotplot(resamps, metric = "RMSE")