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Generate Parameter Names for Mixture Model

Source: R/utils.R
gen_parnames.Rd

This function generates parameter names for a Gaussian mixture model based on the number of components (np) and the order of the polynomial function (sd_ord) used to model the standard deviation parameters.

Usage

gen_parnames(np, sd_ord)

Arguments

np

Integer. The number of Gaussian components in the mixture model.

sd_ord

Integer. The order of the polynomial function used to model the standard deviation parameters. Possible values are:

  • 1: Linear function.

  • 2: Quadratic function.

Value

A character vector of parameter names, including:

  • Logit-transformed probabilities (logitprob_1, ..., logitprob_(np-1)).

  • Mean parameters (mu_int_1, mu_slope_1, ..., for each component).

  • Log-transformed standard deviations (logsd_.1_1, logsd_.L_1, ..., depending on sd_ord and np).

Examples

# Generate parameter names for a 3-component mixture with linear standard deviation function
gen_parnames(np = 3, sd_ord = 1)
#>  [1] "logitprob_1" "logitprob_2" "mu_int_1"    "mu_int_2"    "mu_int_3"   
#>  [6] "mu_slope_1"  "mu_slope_2"  "mu_slope_3"  "logsd_.1_1"  "logsd_.1_2" 
#> [11] "logsd_.1_3"  "logsd_.L_1"  "logsd_.L_2"  "logsd_.L_3" 

# Generate parameter names for a 4-component mixture with quadratic standard deviation function
gen_parnames(np = 4, sd_ord = 2)
#>  [1] "logitprob_1" "logitprob_2" "logitprob_3" "mu_int_1"    "mu_int_2"   
#>  [6] "mu_int_3"    "mu_int_4"    "mu_slope_1"  "mu_slope_2"  "mu_slope_3" 
#> [11] "mu_slope_4"  "logsd_.1_1"  "logsd_.1_2"  "logsd_.1_3"  "logsd_.1_4" 
#> [16] "logsd_.L_1"  "logsd_.L_2"  "logsd_.L_3"  "logsd_.L_4"  "logsd_.Q_1" 
#> [21] "logsd_.Q_2"  "logsd_.Q_3"  "logsd_.Q_4"