Drop variable

Drops columns in a matrix to avoid perfect multicollinearity.

Usage

dropvar(x, tol=1e-07, LAPACK=FALSE, silent=FALSE)

Arguments

x: a matrix, possibly less than full column rank.
tol: numeric value. The tolerance for detecting linear dependencies among regressors, see qr function. Only used if LAPACK is FALSE
LAPACK: logical, TRUE or FALSE (default). If true use LAPACK otherwise use LINPACK, see qr function
silent: logical, TRUE (default) or FALSE. Whether to print a notification whenever a regressor is removed

Value

a matrix whose regressors linearly independent

Details

Original function drop.coef developed by Rune Haubo B. Christensen in package ordinal, https://cran.r-project.org/package=ordinal.

References

Rune H.B. Christensen (2014): 'ordinal: Regression Models for Ordinal Data'. https://cran.r-project.org/package=ordinal

Author

Rune Haubo B. Christensen, with modifications by Genaro Sucarrat, http://www.sucarrat.net/

Examples

set.seed(1)
x <- matrix(rnorm(20), 5)
dropvar(x) #full rank, none are dropped
#>            [,1]       [,2]       [,3]        [,4]
#> [1,] -0.6264538 -0.8204684  1.5117812 -0.04493361
#> [2,]  0.1836433  0.4874291  0.3898432 -0.01619026
#> [3,] -0.8356286  0.7383247 -0.6212406  0.94383621
#> [4,]  1.5952808  0.5757814 -2.2146999  0.82122120
#> [5,]  0.3295078 -0.3053884  1.1249309  0.59390132

x[,4] <- x[,1]*2
dropvar(x) #less than full rank, last column dropped
#> regressor-matrix is column rank deficient, so dropping 1 regressors
#> 
#>            [,1]       [,2]       [,3]
#> [1,] -0.6264538 -0.8204684  1.5117812
#> [2,]  0.1836433  0.4874291  0.3898432
#> [3,] -0.8356286  0.7383247 -0.6212406
#> [4,]  1.5952808  0.5757814 -2.2146999
#> [5,]  0.3295078 -0.3053884  1.1249309