Run a glm model in a pipe

These functions are wrappers for the glm function. The zglm function can be used to estimate any generalized linear model in a pipe. The zlogit, zprobit, and zpoisson functions can be used to estimate specific models. All of these functions rely on the glm function for the actual estimation, they simply pass the corresponding values to the family parameter of the glm function.

Usage of these functions is very similar to the zlm function (a wrapper for lm), for detailed examples, check out the entry for that function.

The zlogit function calls zglm, specifying family=binomial(link="logit").

The zprobit function calls zglm, specifying family=binomial(link="probit").

The zpoisson function calls zglm, specifying family="poisson".

Usage

zglm(
  data,
  formula,
  family = gaussian,
  weights,
  subset,
  na.action,
  start = NULL,
  etastart,
  mustart,
  offset,
  control = list(...),
  model = TRUE,
  method = "glm.fit",
  x = FALSE,
  y = TRUE,
  singular.ok = TRUE,
  contrasts = NULL,
  ...
)

zlogit(data, formula, ...)

zprobit(data, formula, ...)

zpoisson(data, formula, ...)

Arguments

data: A data.frame containing the model data.
formula: The formula to be fitted.
family: See the glm function.
weights: See the glm function.
subset: See the glm function.
na.action: See the glm function.
start: See the glm function.
etastart: See the glm function.
mustart: See the glm function.
offset: See the glm function.
control: See the glm function.
model: See the glm function.
method: See the glm function.
x: See the glm function.
y: See the glm function.
singular.ok: See the glm function.
contrasts: See the glm function.
...: Other arguments to be passed to the glm function.

Value

A fitted model.

Run a glm model in a pipe

Usage

Arguments

Value

See also