How to get result of package function into a dataframe in r

Question

I am at the learning stage of r. I am using library(usdm) in r where I am using vifcor(vardata,th=0.4,maxobservations =50000) to find the not multicollinear variables. I need to get the result of vifcor(vardata,th=0.4,maxobservations =50000) into a structured dataframe for further analysis.

Data reading process I am using:

performdata <- read.csv('F:/DGDNDRV_FINAL/OutputTextFiles/data_blk.csv')
vardata <-performdata[,c(names(performdata[5:length(names(performdata))-2])]

Content of the csv file:

pointid grid_code   Blocks_line_dst_CHT GrowthCenter_dst_CHT    Roads_nationa_dst_CHT   Roads_regiona_dst_CHT   Settlements_CHT_line_dst_CHT    Small_Hat_Bazar_dst_CHT Upazilla_lin_dst_CHT    resp
1   6   150 4549.428711 15361.31836 3521.391846 318.9043884 3927.594727 480 1
2   6   127.2792206 4519.557617 15388.68457 3500.24292  342.0526123 3902.883545 480 1
3   2   161.5549469 4484.473145 15391.6377  3436.539063 335.4101868 3844.216553 540 1

My tries:

• r<-vifcor(vardata,th=0.2,maxobservations =50000) returns

 2 variables from the 6 input variables have collinearity problem: Roads_regiona_dst_CHT GrowthCenter_dst_CHT After excluding the collinear variables, the linear correlation coefficients ranges between: min correlation ( Small_Hat_Bazar_dst_CHT ~ Roads_nationa_dst_CHT ): -0.04119076963 max correlation ( Small_Hat_Bazar_dst_CHT ~ Settlements_CHT_line_dst_CHT ): 0.1384278434 ---------- VIFs of the remained variables -------- Variables VIF 1 Blocks_line_dst_CHT 1.026743892 2 Roads_nationa_dst_CHT 1.010556752 3 Settlements_CHT_line_dst_CHT 1.038307666 4 Small_Hat_Bazar_dst_CHT 1.026943711 

• class(r) returns

 [1] "VIF" attr(,"package") [1] "usdm" 

• mode(r) returns "S4"

I need Roads_regiona_dst_CHT GrowthCenter_dst_CHT into a dataframe and VIFs of the remained variables into another dataframe!

But nothing worked!

Answer 1

You should be able to use the below command to get the information in the slot 'results' into a data frame. You can then split the information out into separate data frames using traditional methods

df <- r@results

Note that r@results[1:2,2] would give you the VIF for the first two rows.

Answer 2

Basically the resturned result is a S4 class and you can extract slots via the @ operator:

library(usdm)
example(vifcor) # creates 'v2'
str(v2)
# Formal class 'VIF' [package "usdm"] with 4 slots
#   ..@ variables: chr [1:10] "Bio1" "Bio2" "Bio3" "Bio4" ...
#   ..@ excluded : chr [1:5] "Bio5" "Bio10" "Bio7" "Bio6" ...
#   ..@ corMatrix: num [1:5, 1:5] 1 0.0384 -0.3011 0.0746 0.7102 ...
#   .. ..- attr(*, "dimnames")=List of 2
#   .. .. ..$ : chr [1:5] "Bio1" "Bio2" "Bio3" "Bio8" ...
#   .. .. ..$ : chr [1:5] "Bio1" "Bio2" "Bio3" "Bio8" ...
#   ..@ results  :'data.frame':   5 obs. of  2 variables:
#   .. ..$ Variables: Factor w/ 5 levels "Bio1","Bio2",..: 1 2 3 4 5
#   .. ..$ VIF      : num [1:5] 2.09 1.37 1.25 1.27 2.31

So you can extract the results and the excluded slot now via:

v2@excluded
# [1] "Bio5"  "Bio10" "Bio7"  "Bio6"  "Bio4"
v2@results
#   variables      VIF
# 1      Bio1 2.086186
# 2      Bio2 1.370264
# 3      Bio3 1.253408
# 4      Bio8 1.267217
# 5      Bio9 2.309479