tpxg.reg: Estimation of log-link TPXG regression coefficients.

In TPXG: Two Parameter Xgamma & Poisson Xgamma: Regression & Distribution Functions

Estimation of log-link TPXG regression coefficients.

Description

This function estimates the Two Parameter Xgamma regression coefficients as well as the \alpha parameter of the Two Parameter Xgamma distribution using the maximum likelihood method.

Usage

tpxg.reg(y,x)

Arguments

y	A numeric vector containg strictly positive values.
x	A matrix or a data.frame with the predictor variables.

Details

This implementation employs a logarithmic link function to relate the \theta parameter of the Two-Parameter Xgamma distribution to the predictor variables. Specifically, the relationship is defined as:

\theta=e^{X\beta}

where X is a matrix whose columns represent the predictor variables, and \beta is a column vector of corresponding regression coefficients.

Value

A named list containing \alpha parameter, a vector containing the \beta coefficients and the maximum likelihood value.

Author(s)

Nikolaos Kontemeniotis.

R implementation and documentation: Nikolaos Kontemeniotis [e-mail] and Michail Tsagris [e-mail].

References

"Sen, S., Chandra, N. and Maiti, S. S. (2018). On properties and applications of a two-parameter XGamma distribution. Journal of Statistical Theory and Applications, 17(4): 674–685."

See Also

tpxg.mle

Examples

x <- matrix( rnorm(100 * 2), ncol = 2 )
y <- rtpxg(100)
tpxg.reg(y, x)

TPXG documentation built on April 3, 2025, 10:37 p.m.