TPXG (version 1.0)

Maximum Likelihood Estimation of TPXG Regression Coefficients: 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)

Value

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

Arguments

y

A numeric vector containg strictly positive values.

x

A matrix or a data.frame with the predictor variables.

Author

Nikolaos Kontemeniotis.

R implementation and documentation: Nikolaos Kontemeniotis and Michail Tsagris .

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.

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)