TFM: The TFM function is to generate Truncated factor model data.

In TFM: Sparse Online Principal Component for Truncated Factor Model

The TFM function is to generate Truncated factor model data.

Description

The TFM function generates truncated factor model data supporting various distribution types for related analyses using multiple methods.

Usage

TFM(n, mu, sigma, lower, upper, distribution_type)

Arguments

n	Total number of observations.
mu	The mean of the distribution.
sigma	The parameter of the distribution.
lower	The lower bound of the interval.
upper	The upper bound of the interval.
distribution_type	String specifying the distribution type to use.

Value

A list containing:

X	A matrix of generated truncated factor model data based on the specified distribution type. Each row corresponds to an observation, and each column corresponds to a variable.

Examples

library(relliptical)
set.seed(123)
mu <- c(0, 1)
n <- 100
sigma <- matrix(c(1, 0.70, 0.70, 3), 2, 2)
lower <- c(-2, -3)
upper <- c(3, 3)
distribution_type <- "truncated_normal"
X <- TFM(n, mu, sigma, lower, upper, distribution_type)

TFM documentation built on June 9, 2025, 9:08 a.m.