Negative binomial regression
Negative binomial regression.
negbin.reg(y, x, tol = 1e-07, maxiters = 100)
y |
The dependent variable, a numerical vector with integer valued numbers. |
x |
A matrix or a data.frame with the indendent variables. |
tol |
The tolerance value required by the Newton-Raphson to stop. |
maxiters |
The maximum iterations allowed. |
A negative binomial regression model is fitted. The standard errors of the regressions are not returned as we do not compute the full Hessian matrix at each step of the Newton-Raphson.
A list including:
be |
The regression coefficients. |
loglik |
The loglikelihood of the regression model. |
iters |
The iterations required by the Newton-Raphson. |
Michail Tsagris
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Stefanos Fafalios stefanosfafalios@gmail.com.
y <- rnbinom(100, 10, 0.7) x <- matrix( rnorm(100 * 3), ncol = 3 ) mod <- negbin.reg(y, x)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.