12_12_report

Author

Isaac

options(warn = -1)

library(dplyr)


Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(lmerTest)

Loading required package: lme4

Loading required package: Matrix


Attaching package: 'lmerTest'

The following object is masked from 'package:lme4':

    lmer

The following object is masked from 'package:stats':

    step

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats   1.0.0     ✔ readr     2.1.5
✔ ggplot2   3.5.1     ✔ stringr   1.5.1
✔ lubridate 1.9.3     ✔ tibble    3.2.1
✔ purrr     1.0.2     ✔ tidyr     1.3.1

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ tidyr::expand() masks Matrix::expand()
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
✖ tidyr::pack()   masks Matrix::pack()
✖ tidyr::unpack() masks Matrix::unpack()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(modelr)
library(purrr)
library(emmeans)

Welcome to emmeans.
Caution: You lose important information if you filter this package's results.
See '? untidy'

library(gridExtra)


Attaching package: 'gridExtra'

The following object is masked from 'package:dplyr':

    combine

library(writexl)
library(gt)
library(webshot2)
library(broom.mixed)
library(ggplot2)

load("Z:/Isaac/Visual Features/data/all_objects_12_11.RData")

plots for the mean value residuals accounting for hour of the day

options(repr.plot.width = 16, repr.plot.height = 250)
library(ggforce)
for (i in 1:5){
  p1<- ggplot(aug_res_10,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("10 min window mean")+
        theme_void()
  print(p1)
  p2<- ggplot(aug_res_20,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("20 min window mean")+
        theme_void()
  print(p2)
  p3<- ggplot(aug_res_30,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("30 min window mean")+
        theme_void()
  print(p3)
  p4<- ggplot(aug_res_60,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("60 min window mean")+
        theme_void()
  print(p4)
}

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

load("Z:/Isaac/Visual Features/data/all_objects_12_12.RData")

plots for the mean value residuals accounting for hour of the day

for (i in 1:5){
  p1<- ggplot(aug_res_10_var,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("10 min window var")+
        theme_void()
  print(p1)
  p2<- ggplot(aug_res_20_var,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("20 min window var")+
        theme_void()
  print(p2)
  p3<- ggplot(aug_res_30_var,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("30 min window var")+
        theme_void()
  print(p3)
  p4<- ggplot(aug_res_60_var,aes(x=ttf,y=.resid,color=sow))+
        geom_smooth(se=F)+
        geom_smooth(aes(x=ttf,y=.resid),linewidth=1.2,color="black")+
        facet_wrap_paginate(~feature,scales="free",ncol=2,nrow=2,page=i)+
        ggtitle("60 min window var")+
        theme_void()
  print(p4)
}

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'

Notes

get rid of warnings for rendering document the residual calculation and have it match up with the fitted value or whatever to get the resid filter the data to atleast have a full day of recording try putting the ttf as response ttf~hour+(1|sow)+feature(s) features could vary, many to few step BIC survival analysis cox regression response is all 0 and 1 with 1 for farrowing 1 stop at the end of farrowing