I am going to winsorize my dataset to get rid of some outliers with the package robustHD. It is the first time I ran into this error. The dataset contains 50+ variables and 100+ observations.
How can I fix this? And why matrix singularity matters for a calculation like winsorize? Thanks.
df_win<-winsorize(df,prob=0.95)
Error in solve.default(R) : system is computationally singular: reciprocal condition number = 1.26103e-18
The reason for this is that winsorize in robustHD uses solve. If you look deeper into the code, winsorize on a data frame calls the winsorize.data.frame method, which is simply a script that runs as.matrix and then uses the winsorize.matrix method. This in turns does a bunch of things, but the problem here is that it uses the solve function.
The error you get is from solve. The error probably occurs because you included some variables/columns that are very highly correlated, or rather, they are linear combinations of each other. You may want to check if you have duplicated variables or variables that are transformations of each other.
There are several things you can do:
winsorize from. The quickest way to do the second step:
require(sos)
findFn("winsorize")
This will produce an overview of all functions that have the word "winsorize" in their description. Just look for functions that are described to be used for winsorization.
