Merge pull request #440 from spsanderson/development

Fixes #420

Author: spsanderson

NAMESPACE

@@ -96,6 +96,7 @@ export(util_burr_param_estimate)
 export(util_burr_stats_tbl)
 export(util_cauchy_param_estimate)
 export(util_cauchy_stats_tbl)
+export(util_chisq_aic)
 export(util_chisquare_param_estimate)
 export(util_chisquare_stats_tbl)
 export(util_exponential_param_estimate)

R/utils-aic-chisq.R

@@ -0,0 +1,57 @@
+#' Calculate Akaike Information Criterion (AIC) for Chi-Square Distribution
+#'
+#' This function calculates the Akaike Information Criterion (AIC) for a chi-square distribution fitted to the provided data.
+#'
+#' @family Utility
+#' @author Steven P. Sanderson II, MPH
+#'
+#' @description
+#' This function estimates the parameters of a chi-square distribution from the provided data using maximum likelihood estimation,
+#' and then calculates the AIC value based on the fitted distribution.
+#'
+#' @param .x A numeric vector containing the data to be fitted to a chi-square distribution.
+#'
+#' @examples
+#' # Example 1: Calculate AIC for a sample dataset
+#' data <- c(1, 2, 3, 4, 5)
+#' util_chisq_aic(data)
+#'
+#' @return
+#' The AIC value calculated based on the fitted chi-square distribution to the provided data.
+#'
+#' @name util_chisq_aic
+#'
+#' @export
+#' @rdname util_chisq_aic
+util_chisq_aic <- function(.x) {
+  # Tidyeval
+  x <- as.numeric(.x)
+
+  # Get parameters
+  pe <- TidyDensity::util_chisquare_param_estimate(x)$parameter_tbl |> head(1)
+
+  # Negative log-likelihood function for chi-square distribution
+  neg_log_lik_chisq <- function(par, data) {
+    df <- par[1]
+    ncp <- par[2]
+    n <- length(data)
+    -sum(stats::dchisq(data, df = df, ncp = ncp, log = TRUE))
+  }
+
+  # Fit chi-square distribution to sample data (rchisq)
+  fit_chisq <- optim(
+    c(pe$degrees_of_freedom, pe$ncp),
+    neg_log_lik_chisq,
+    data = x
+  )
+
+  # Extract log-likelihood and number of params
+  logLik_chisq <- -fit_chisq$value
+  k_chisq <- 2  # Number of parameters for chi-square distribution (degrees of freedom or df)
+
+  # Calculate AIC
+  AIC_chisq <- 2 * k_chisq - 2 * logLik_chisq
+
+  # Return
+  return(AIC_chisq)
+}