Package 'TLIC'

Title: The LIC for T Distribution Regression Analysis
Description: This comprehensive toolkit for T-distributed regression is designated as "TLIC" (The LIC for T Distribution Regression Analysis) analysis. It is predicated on the assumption that the error term adheres to a T-distribution. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02664763.2022.2053949>.
Authors: Guangbao Guo [aut, cre] , Guofu Jing [aut]
Maintainer: Guangbao Guo <[email protected]>
License: MIT + file LICENSE
Version: 0.3
Built: 2024-10-30 09:21:50 UTC
Source: CRAN

Help Index


terr function is used to generate a dataset where the error term follows a T-distribution

Description

This terr function generates a dataset with a specified number of observations and predictors, along with a response vector that has an error term following a T-distribution.

Usage

terr(n, nr, p, dist_type, ...)

Arguments

n

is the number of observations

nr

is the number of observations with a different error T distribution

p

is the dimension of the observation

dist_type

is the type where the error term obeys a T-distribution

...

is additional arguments for the T-distribution function

Value

X,Y,e

Examples

set.seed(12)
data <- terr(n = 1200, nr = 200, p = 5, dist_type = "student_t")
str(data)

TLIC function based on LIC with T-distributed errors

Description

The TLIC function builds on the LIC function by introducing the assumption that the error term follows a T-distribution, thereby enhancing the length and information optimisation criterion.

Usage

TLIC(X, Y, alpha = 0.05, K = 10, nk = NULL, dist_type = "student_t")

Arguments

X

is a design matrix

Y

is a random response vector of observed values

alpha

is the significance level

K

is the number of subsets

nk

is the sample size of subsets

dist_type

is the type where the error term obeys a T-distribution

Value

MUopt, Bopt, MAEMUopt, MSEMUopt, opt, Yopt

Examples

set.seed(12)
n <- 1200
nr <- 200
p <- 5
data <- terr(n, nr, p, dist_type = "student_t")
TLIC(data$X, data$Y, alpha = 0.05, K = 10, nk = n / 10, dist_type = "student_t")