hp.reg: Hurdle-Poisson regression

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/regression_models.R

Description

Hurdle-Poisson regression.

Usage

1
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 <mtsagris@uoc.gr>

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

1
2
3
y <- rpois(100, 4)
x <- iris[1:100, 1]
a <- hp.reg(y, x)

Rfast2 documentation built on March 22, 2021, 9:08 a.m.