| Hurdle-Poisson regression {Rfast2} | R Documentation |
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 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
Examples
y <- rpois(100, 4)
x <- iris[1:100, 1]
a <- hp.reg(y, x)