binom.reg: Binomial regression

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

Binomial regression

Description

Binomial regression.

Usage

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

Arguments

y	The dependent variable; a numerical vector with integer values, 0, 1, 2,... The successes.
ni	A vector with integer values, greater than or equal to y. The trials.
x	A matrix with the data, where the rows denote the samples (and the two groups) and the columns are the variables. This can be a matrix or a data.frame (with factors).
full	If this is FALSE, the coefficients and the deviance 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

The difference from logistic regression is that in the binomial regression the binomial distribution is used and not the Bernoulli.

Value

When full is FALSE a list including:

be	The regression coefficients.
devi	The deviance of the model.

When full is TRUE a list including:

info	The regression coefficients, their standard error, their Wald test statistic and their p-value.
devi	The deviance.

Author(s)

Michail Tsagris.

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

References

McCullagh Peter and John A. Nelder. Generalized linear models. CRC Press, USA, 2nd edition, 1989.

See Also

negbin.reg, hp.reg, ztp.reg

Examples

x <- matrix(rnorm(100 * 2), ncol = 2)
y <- rbinom(100, 20, 0.5)   ## binary logistic regression
ni <- rep(20, 100)
a <- binom.reg(y, ni, x, full = TRUE) 
x <- NULL

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