Simulate an example

Simulate an example

Usage

run_example(n = 5000)

Arguments

n

number of samples

Value

a list containing data (the dataset generated), em_results (the output of EM_spherical_gaussians), and probabilities (the output of compute_probabilities)

This program uses the following functions: generate_mixture_gaussians, EM_spherical_gaussians, and compute_probabilities.

See also

generate_mixture_gaussians(), EM_spherical_gaussians(), and compute_probabilities()

Examples

res <- run_example()
res$em_results
#> $means
#>              [,1]        [,2]
#> [1,]  2.000675688  1.98424467
#> [2,] -0.002657805 -0.03816044
#> [3,]  5.047867139  4.97657474
#> 
#> $variances
#> [1] 0.1244912 0.9799054 1.4883660
#> 
#> $proportions
#> [1] 0.4050738 0.2035087 0.3914176
#> 
#> $log_likelihood
#> [1] -1.376677e-14
#>