outlierCARBayesST

a function to detect outlier point in time-course using a CARBayesST modelling

outlierCARBayesST(modelin, datain, threshold, trait)

Arguments

modelin

a CARBayesST object
datain

input dataframe of parameters used in the CARBayesST modelling
threshold,

numeric threshold for influence with standardized residuals
trait,

character, trait of interest to model (example plantHeight...)

Value

a plot of fitted vs. residuals and a dataset with a column identifying the outlier points

See also

CARBayesST, ST.CARanova

Examples

# \donttest{
 data(plant1)
 library(dplyr)
 mydata<-filter(plant1,!is.na(plant1$thermalTime))
 str(mydata)
#> 'data.frame':	45342 obs. of  14 variables:
#>  $ Ref            : Factor w/ 1680 levels "manip1_10_10_WW",..: 131 131 131 131 131 131 131 131 131 131 ...
#>  $ experimentAlias: Factor w/ 1 level "manip1": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ Day            : Factor w/ 42 levels "2013-02-01","2013-02-02",..: 3 4 5 6 7 9 9 10 11 12 ...
#>  $ potAlias       : int  1 1 1 1 1 1 1 1 1 1 ...
#>  $ scenario       : Factor w/ 2 levels "WD","WW": 2 2 2 2 2 2 2 2 2 2 ...
#>  $ genotypeAlias  : Factor w/ 274 levels "11430_H","A310_H",..: 165 165 165 165 165 165 165 165 165 165 ...
#>  $ repetition     : int  1 1 1 1 1 1 1 1 1 1 ...
#>  $ Line           : int  1 1 1 1 1 1 1 1 1 1 ...
#>  $ Position       : int  1 1 1 1 1 1 1 1 1 1 ...
#>  $ thermalTime    : num  1.29 2.65 3.98 5.32 6.66 ...
#>  $ plantHeight    : num  140 151 213 239 271 ...
#>  $ leafArea       : num  0.018 0.019 0.0208 0.0222 0.0235 ...
#>  $ biovolume      : num  0.253 0.62 1.201 1.68 3.396 ...
#>  $ Repsce         : Factor w/ 15 levels "1_WD","1_WW",..: 2 2 2 2 2 2 2 2 2 2 ...
 test<-fitCARBayesST(datain=mydata,xvar="thermalTime",
       trait="plantHeight",k=2,
       graphDist=TRUE,burnin=10,n.sample=110,
       formulaModel=as.formula(plantHeight~scenario+genotypeAlias),
       typeModel="anova",verbose=FALSE)
#> [1] 22.35558
#>            used  (Mb) gc trigger   (Mb) max used  (Mb)
#> Ncells  3935847 210.2    6893817  368.2  3935847 210.2
#> Vcells 68236062 520.6  203368829 1551.6 68236062 520.6
 test2<-outlierCARBayesST(modelin=test[[1]],datain=test[[2]],threshold=4,
        trait="plantHeight")
# }