Extract various sigma matrices

cov_mat(obj, which = c("xy", "zy", "zw"), use_population = TRUE)

Arguments

obj	A simrel object
which	A character string to specify which covariance matrix to extract, possible values are "xy", "zy" and "zw"
use_population	A boolean whether to use compute population values or to estimate from sample

Value

A matrix of covariances with column equals to the number of response and row equals to the number of predictors

Examples

set.seed(1983)
sobj <- multisimrel()
cov_mat(sobj, which = "xy", use_population = TRUE)
#>              [,1]        [,2]        [,3]        [,4]        [,5]
#>  [1,]  0.05473538  0.00000000  0.00000000  0.00000000  0.00000000
#>  [2,]  0.44858369  0.00000000  0.00000000  0.00000000  0.00000000
#>  [3,]  0.00000000 -0.10890699  0.00000000  0.00000000  0.10890699
#>  [4,]  0.00000000  0.02184183  0.00000000  0.00000000 -0.02184183
#>  [5,]  0.00000000  0.00000000  0.01324199 -0.01324199  0.00000000
#>  [6,]  0.00000000  0.19497385  0.00000000  0.00000000 -0.19497385
#>  [7,]  0.00000000  0.00000000  0.10910888 -0.10910888  0.00000000
#>  [8,]  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000
#>  [9,] -0.47857313  0.00000000  0.00000000  0.00000000  0.00000000
#> [10,] -0.38466577  0.00000000  0.00000000  0.00000000  0.00000000
#> [11,]  0.00000000  0.00000000 -0.12235087  0.12235087  0.00000000
#> [12,]  0.35991983  0.00000000  0.00000000  0.00000000  0.00000000
#> [13,]  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000
#> [14,]  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000
#> [15,]  0.00000000 -0.10790869  0.00000000  0.00000000  0.10790869
cov_mat(sobj, which = "xy", use_population = FALSE)
#>                [,1]          [,2]         [,3]         [,4]         [,5]
#>  [1,]  0.1499094276  0.0225551020 -0.021142532 -0.017642244  0.009116718
#>  [2,]  0.3270660152 -0.0537449359 -0.033024128 -0.036275335  0.016893383
#>  [3,] -0.0113945975 -0.0636098314  0.019111991  0.046077320  0.059385293
#>  [4,]  0.0767651573 -0.0019784663 -0.029996310 -0.032876966  0.028271693
#>  [5,]  0.0222361281  0.0075803695  0.022482684 -0.006324240  0.005639610
#>  [6,] -0.0141878957  0.1413595087 -0.003967554 -0.064016125 -0.172939042
#>  [7,] -0.0115258345  0.0227697907  0.098918022 -0.119249383  0.011651468
#>  [8,]  0.0027930961  0.0021889811 -0.002523865 -0.005940305  0.003180998
#>  [9,] -0.4569019775  0.0246946536  0.076264713  0.053941713 -0.019426372
#> [10,] -0.3785386131  0.0221709535  0.041538158  0.050496291 -0.023458174
#> [11,] -0.0008586489 -0.0185189080 -0.109589395  0.115398439 -0.005525881
#> [12,]  0.3642008527 -0.0188607949 -0.063248293 -0.052700939  0.009243102
#> [13,] -0.0007261248  0.0008247841  0.008077454 -0.004486281  0.002823606
#> [14,] -0.0057113104 -0.0065983306 -0.004226565  0.009044024 -0.005520259
#> [15,] -0.0482433762 -0.0719015998  0.017384308  0.049231552  0.088036807