draw_from_pdf: Draw Samples Using Inverse Transform Sampling

In dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models

Draw Samples Using Inverse Transform Sampling

Description

draw_from_pdf generates samples from a given probability density function (PDF) using inverse transform sampling. This function takes in a numeric PDF vector and a corresponding domain vector, then returns a specified number of samples.

Usage

draw_from_pdf(a_pdf, x_def, k, seed = NULL, round_to = NULL, method = "discr")

Arguments

a_pdf	a numeric vector representing the PDF values.
x_def	a numeric vector defining the domain (or x-values) corresponding to the values in a_pdf. The vector x_def must be sorted in increasing order.
k	a single integer specifying the number of samples to generate.
seed	an optional single integer value used to set the seed for random number generation, allowing for reproducibility of results.
round_to	an optional integer, indicating the number of digits to which the result should be rounded.
method	a single character string. If "discr", then simulated values match x_def. If "linear", x_def and a_pdf are linearly interpolated, so that the simulated values can lay in between the discrete values of x_def.

Details

This function implements inverse transform sampling by first constructing a cumulative distribution function (CDF) from the given PDF. Then k values between zero and one are sampled from a uniform distribution, and the corresponding values are mapped to x_def using linear interpolation.

Value

A numeric vector of length k containing the sampled values from the specified PDF. If k is 0, an empty numeric vector is returned.

dRiftDM documentation built on Dec. 1, 2025, 5:08 p.m.