glm.binomial: Creates a Binomial GLM family object.

In adelie: Group Lasso and Elastic Net Solver for Generalized Linear Models

Creates a Binomial GLM family object.

Description

A GLM family object specifies the type of model fit, provides the appropriate response object and makes sure it is represented in the right form for the model family, and allows for optional parameters such as a weight vector.

Usage

glm.binomial(y, weights = NULL, link = "logit")

Arguments

y	Binary response vector, with values 0 or 1, or a logical vector. Alternatively, if data are represented by a two-column matrix of proportions (with row-sums = 1), then one can provide one of the columns as the response. This is useful for grouped binomial data, where each observation represents the result of m[i] successes out of n[i] trials. Then the response is provided as y[i] = m[i]/n[i] and the corresponding element of the weight vector as w[i]=n[i]. Alternatively can use glm.multinomial() instead.
weights	Observation weight vector, with default NULL.
link	The link function type, with choice "logit" (default) or "probit").

Value

Binomial GLM object.

Author(s)

Trevor Hastie and James Yang
Maintainer: Trevor Hastie [e-mail]

See Also

glm.gaussian, glm.binomial, glm.poisson, glm.multinomial, glm.multigaussian, glm.cox.

Examples

n <- 100
y <- rbinom(n, 1, 0.5)
obj <- glm.binomial(y)

adelie documentation built on Sept. 11, 2024, 6:36 p.m.