# Plot Multiple Fitted Distributions Creates 2x2 plots for multiple fitted distributions: Fitted PDFs, Fitted CDFs vs Empirical CDF, QQ-Plots, and PP-Plots. ```r plot_multi_fitted( data, pdf_list, cdf_list, qf_list, params_list, dist_names = NULL, col_list = NULL, lty_list = NULL, lwd_list = NULL, main_pdf = "Fitted PDFs", main_cdf = "Fitted CDFs", main_qq = "QQ Plots", main_pp = "PP Plots", xlab = "x" ) ``` ## Arguments - `data`: Numeric vector of observed data. - `pdf_list`: List of PDF functions. Each function should take `x` and `par`. - `cdf_list`: List of CDF functions. Each function should take `x` and `par`. - `qf_list`: List of quantile functions (inverse CDF). Each function should take `p` and `par`. - `params_list`: List of parameter vectors corresponding to each distribution. - `dist_names`: Optional vector of distribution names. - `col_list`: Optional vector of colors for each distribution. - `lty_list`: Optional vector of line types for each distribution. - `lwd_list`: Optional vector of line widths for each distribution. - `main_pdf`: Title for PDF plot. - `main_cdf`: Title for CDF plot. - `main_qq`: Title for QQ plot. - `main_pp`: Title for PP plot. - `xlab`: Label for x-axis. ## Returns NULL (plots are generated as a side effect) ## Examples ```r # Example Multiple Distributions set.seed(1) data <- rexp(200, 1.1) # Exponential pdf_exp <- function(x, par) par[1] * exp(-par[1] * x) cdf_exp <- function(x, par) 1 - exp(-par[1] * x) qf_exp <- function(p, par) -log(1 - p) / par[1] # Generalized Exponential pdf_gexp <- function(x, par) { a <- par[1]; l <- par[2] a * l * exp(-l*x) * (1-exp(-l*x))^(a-1) } cdf_gexp <- function(x, par) { a <- par[1]; l <- par[2] (1-exp(-l*x))^a } qf_gexp <- function(p, par) { a <- par[1]; l <- par[2] -log(1 - p^(1/a)) / l } # Weibull pdf_weibull <- function(x, par) { k <- par[1]; l <- par[2] (k/l) * (x/l)^(k-1) * exp(-(x/l)^k) } cdf_weibull <- function(x, par) { k <- par[1]; l <- par[2] 1 - exp(-(x/l)^k) } qf_weibull <- function(p, par) { k <- par[1]; l <- par[2] l * (-log(1 - p))^(1/k) } # Normal pdf_norm <- function(x, par) dnorm(x, par[1], par[2]) cdf_norm <- function(x, par) pnorm(x, par[1], par[2]) qf_norm <- function(p, par) qnorm(p, par[1], par[2]) data <- rexp(200, 1) # Call the plot function plot_multi_fitted( data = data, pdf_list = list(pdf_exp, pdf_gexp, pdf_weibull, pdf_norm), cdf_list = list(cdf_exp, cdf_gexp, cdf_weibull, cdf_norm), qf_list = list(qf_exp, qf_gexp, qf_weibull, qf_norm), params_list = list( c(1.1), c(2, 1.3), c(1.5, 2), c(0, 1) ), dist_names = c("Exp", "GExp", "Weibull", "Normal"), col_list = c("blue", "red", "darkgreen", "purple"), lty_list = c(1, 2, 3, 4), lwd_list = c(3, 3, 3, 3) ) ```

plot_multi_fitted function