MJacobs1985

plot_model(fit.4, grid=T, type="diag")
plot_model(fit.1, grid=T, sort.est="sort.all", y.offset=1.0)
plot_model(fit.1, type="eff")
plot_model(fit.1, show.values = TRUE, value.offset = .3)
plot_model(fit.1, type="re") 
plot_model(fit.1, type="std")  
plot_model(fit.1, type="resid")
plot_model(fit.1, type="pred", grid=T, terms=c("curve_day [all]"))
tab_model(fit.1, 
          show.std=T, 

MJacobs1985

dfnew2<-dfnew%>%dplyr::select(curve_day, ogn_id, 
                              lcn_id, feed_provided, 
                              feed_provided_cum, newField, 
                              animals_actual)%>%na.omit
fit.1<-lmer(feed_provided_cum~ns(curve_day,3)+
            (0+ns(curve_day,2)|newField/lcn_id),
          data=dfnew2)
fit.2<-lmer(feed_provided_cum~ns(curve_day,3)+
              animals_actual+
              (0+ns(curve_day,2)|newField/lcn_id),

MJacobs1985

master_data_tbl <- dfnew %>%
  filter(date_interval>"2021-06-10")%>%
  dplyr::select(feed_provided,
                lcn_id,
                newField,
                date_interval)%>%
  filter(!is.na(date_interval))%>%
  distinct()%>%
  group_by(lcn_id, newField) %>%
  filter(n() >= 30)%>%

MJacobs1985

master_data_tbl <- dfnew %>%
  filter(date_interval>"2021-06-10")%>%
  dplyr::select(feed_provided,
                lcn_id,
                newField,
                date_interval)%>%
  filter(!is.na(date_interval))%>%
  distinct()%>%
  group_by(lcn_id, newField) %>%
  imputeTS::na_kalman(.)%>%

MJacobs1985

#### DATA EXPLORATION ####
ggplot(df,aes(x=date_interval,
                        y=feed_provided, col=as.factor(lcn_id))) + 
  geom_point(alpha=0.1) + 
  theme_bw()+
  facet_wrap(~ogn_id)+
  theme(legend.position = "none")
df%>%
  filter(feed_provided_cum>0)%>%
  ggplot(.,aes(x=date_interval)) + 

MJacobs1985

## Add run identifier for days 
dfcurve<-df%>%
  filter(!is.na(curve_day))
dfcurve<-dfcurve[, colSums(is.na(dfcurve)) != nrow(dfcurve)]

dfnocurve<-df%>%filter(is.na(curve_day) & !is.na(feed_provided_cum))
dfnocurve%>%
  arrange(lcn_id, date_interval)%>%
  group_by(lcn_id)%>%
  mutate(curve_day = ifelse(min(feed_provided_cum), 1, 0))%>%

MJacobs1985

rm(list = ls())
#### LIBRARIES ####
library(readr)
library(readxl)
library(tidyverse)
library(DataExplorer)
library(mice)
library(naniar)
library(skimr)
library(grid)

MJacobs1985

rm(list = ls())
library(tidyverse)
library(readr)
library(ggthemes)
library(lubridate)
library(zoo)
library(gganimate)

getwd()
data_folder <- file.path("C:/Users/marcj/Nutreco/StatisticsPlatform/Website/ELearning/Workshops/CausalAnalysis/Covid/")

MJacobs1985

library(readr)
library(ggplot2)
library(gganimate)
library(tidyverse)
library(ggrepel)
library(lubridate)
library(tidymodels)
library(modeltime)
library(tsbox)
library(TSstudio)

MJacobs1985

library(readr)
library(stringr)
library(tidyverse)
library(zoo)
library(grid)
library(gridExtra)
mygrid <- read_csv("mygrid.csv")
mygrid$icds
datesplit<-str_split(mygrid$icds, "_")
df <- data.frame(matrix(unlist(datesplit), nrow=length(datesplit), byrow=TRUE))