hp.reg: Hurdle-Poisson regression

In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

Hurdle-Poisson regression

Description

Hurdle-Poisson regression.

Usage

hp.reg(y, x, full = FALSE, tol = 1e-07, maxiters = 100) 

Arguments

y	The dependent variable, a numerical vector with numbers.
x	A numerical matrix with the indendent variables. We add, internally, the first column of ones.
full	If this is FALSE, the coefficients and the log-likelihood will be returned only. If this is TRUE, more information is returned.
tol	The tolerance value to terminate the Newton-Raphson algorithm.
maxiters	The max number of iterations that can take place in each regression.

Details

Two regression models are fitted, a binary logistic regression and a zero truncated Poisson regression model.

Value

Depending on whether "full" is TRUE or not different outputs are returned. In general, the regression coefficients, the iterations required by Newton-Raphson and the deviances are returned. If full is TRUE, a matrix with their standard errors and the Wald test statistics is returned as well.

Author(s)

Michail Tsagris.

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

References

Mullahy J (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3): 341–365.

See Also

negbin.reg, ztp.reg

Examples

y <- rpois(100, 4)
x <- iris[1:100, 1]
a <- hp.reg(y, x)

Rfast2 documentation built on May 29, 2024, 8:45 a.m.