gistfile1.txt

dfnew<-as.data.frame(dfnew)
inTraining <- createDataPartition(dfnew$newField, 
                                  p = .75, 
                                  list = FALSE)

training   <- dfnew[ inTraining,]
testing    <- dfnew[-inTraining,]

training%>%
  filter(lcn_id%in%(901:906))%>%
  ggplot(., aes(x=curve_day, 
                y=comp1_provided, 
                colour=as.factor(newField)))+
  geom_point()+
  theme_bw()+
  facet_wrap(~lcn_id, ncol=3)
  
  testing%>%
  group_by(ogn_id,newField, curve_day)%>%
  summarize(sumprov = mean(feed_provided_cum),
            sumpred = mean(pred))%>%
  ggplot(., aes(x=curve_day, 
                fill=newField))+
  geom_area(aes(y=sumprov), alpha=0.5)+
  geom_point(aes(y=sumpred), alpha=0.5)+
  geom_line(aes(y=sumpred))+
  theme_bw()+
  facet_wrap(~ogn_id+newField)


testing%>%
  filter(lcn_id%in%(901:906))%>%
  ggplot(., aes(x=curve_day, 
                y=comp1_provided, 
                colour=as.factor(newField)))+
  geom_point()+
  theme_bw()+
  facet_wrap(~lcn_id, ncol=3)

m1_gam <- gamm4(feed_provided_cum~s(curve_day)+
                s(animals_actual)+
                s(feed_provided)+
                ogn_id+
                newField,
                data=training,
                random=~(1+curve_day|lcn_id))
m1_gam
plot(m1_gam$mer)
par(mfrow = c(2, 2))
plot(m1_gam$gam)
m1_gam_aug<-augment(m1_gam$gam, confint=TRUE)
m1_gam_mer_aug<-augment(m1_gam$mer, confint=TRUE)
m1_gam_aug%>%filter(lcn_id%in%(901:909))%>%
  ggplot(., aes(x=feed_provided_cum, y=.fitted, colour=.resid))+
  geom_point()+
  theme_bw()+
  facet_wrap(~lcn_id+newField)+
  geom_abline(intercept=0, slope=1, lty=2, col="black")+
  scale_color_viridis_c(option="turbo")

m1_gam_mer_aug%>%filter(lcn_id%in%(901:909))%>%
  ggplot(., aes(x=.mu, y=.fitted, colour=.resid))+
  geom_point()+
  theme_bw()+
  geom_abline(intercept=0, slope=1, lty=2, col="black")+
  scale_color_viridis_c(option="turbo")

m1_gam_aug%>%filter(lcn_id%in%(901:920))%>%
  ggplot(., aes(x=curve_day, group=newField))+
  geom_point(aes(y=feed_provided_cum,colour=newField), alpha=0.5)+
  geom_line(aes(y=.fitted, colour=newField), lty=2, lwd=1)+
  theme_bw()+
  facet_wrap(~lcn_id+newField)

m1_gam_aug%>%filter(lcn_id%in%(901:920))%>%
  ggplot(., aes(x=.resid, fill=newField))+
  geom_density(alpha=0.5)+
  geom_vline(xintercept=0, lty=2, col="black")+
  theme_bw()+
  facet_wrap(~lcn_id)

testing$pred<-predict(m1_gam$gam, newdata=testing)
testing%>%filter(lcn_id%in%(901:920))%>%
  ggplot(., aes(x=curve_day, group=newField))+
  geom_point(aes(y=feed_provided_cum,colour=newField), alpha=0.5)+
  geom_line(aes(y=pred, colour=newField), lty=2, lwd=1)+
  theme_bw()+
  facet_wrap(~lcn_id+newField)

testing%>%filter(lcn_id%in%(901:909))%>%
  ggplot(., aes(x=feed_provided_cum, 
                y=pred, 
                colour=feed_provided_cum-pred))+
  geom_point()+
  theme_bw()+
  facet_wrap(~newField)+
  geom_abline(intercept=0, slope=1, lty=2, col="black")+
  scale_color_viridis_c(option="turbo")