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Density of a Normal Mixture Model

Source: R/utils.R
dnormmix.Rd

This function calculates the density of a normal mixture model for a given vector of parameters on the unconstrained scale (softmax(prob), mean, log(sd)).

Usage

dnormmix(x, par, logmean, ..., log = FALSE)

Arguments

x

Numeric vector of values at which to evaluate the density.

par

A vector of parameters on the unconstrained scale, including:

  • softmax(prob): Mixture probabilities (on the unconstrained scale, transformed via softmax).

  • mean: Means of the normal components.

  • log(sd): Logarithms of standard deviations of the normal components.

logmean

Numeric value representing the log of the mean parameter.

...

Additional arguments passed to the genmixpars function. Defaults: two components (np = 2) and a quadratic model for standard deviation parameters (sd_ord = 2).

log

Logical. If TRUE, the logarithm of the density is returned. Default is FALSE.

Value

A numeric vector of density values (or log-density values if log = TRUE) for the mixture model.

Examples

# Example parameters
x <- seq(-3, 3, length.out = 100)
## par <- c(-0.5, 0.5, log(0.8), log(1.2))  # Example: softmax probabilities, mean, log(sd)
set.seed(101); par <- rnorm(11)
logmean <- rep(0.1, length(x))  ## constant log mean

# Calculate density
density <- dnormmix(x, par, logmean)

# Calculate log-density
log_density <- dnormmix(x, par, logmean, log = TRUE)