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Summarizing kernel-based quadratic distance results

Source: R/pk.test.R
summary.pk.test.Rd

summary method for the class pk.test

Usage

# S4 method for class 'pk.test'
summary(object)

Arguments

object

Object of class pk.test

Value

List with the following components:

  • summary_tables Table of computed descriptive statistics per variable.

  • test_results Data frame with the results of the performed Poisson kernel-based test.

  • qqplots Figure with qq-plots for each variable against the uniform distribution.

See also

pk.test() and pk.test for additional details.

Examples

# create a pk.test object
x_sp <- sample_hypersphere(3, n_points=100)
unif_test <- pk.test(x_sp,rho=0.8)
summary(unif_test)
#> 
#>  Poisson Kernel-based quadratic distance test of 
#>                         Uniformity on the Sphere 
#>   Test_Statistics Critical_Value Reject_H0
#> 1     -0.02581372       1.627734     FALSE
#> 2     43.87599858      52.230766     FALSE

#> $summary_tables
#>                 V1         V2          V3
#> mean   -0.05891549  0.1005389 -0.02266109
#> sd      0.59530536  0.5486256  0.58351311
#> median -0.09579144  0.1875468 -0.04974959
#> IQR     1.01860873  0.8751004  1.02478167
#> min    -0.99981089 -0.9760971 -0.92478198
#> max     0.94196356  0.9764094  0.93822530
#> 
#> $test_results
#>   Test_Statistics Critical_Value Reject_H0
#> 1     -0.02581372       1.627734     FALSE
#> 2     43.87599858      52.230766     FALSE
#> 
#> $qqplots

#>