bglm {bigReg} | R Documentation |
Function to carry out generalized linear regression on a data_frame data object
Description
Function to carry out generalized linear regression on a data_frame data object
Usage
bglm(
formula,
family = gaussian_(),
data,
weights = NULL,
offset = NULL,
start = NULL,
control = list(),
etastart = NULL,
mustart = NULL
)
Arguments
formula |
formula that defines your regression model |
family |
family object from activeReg, e.g. .gaussian(), .binomial(), .poisson(), .quasipoisson(), .quasibinomial(), .Gamma(), .inverse.gaussian(), .quasi() |
data |
data_frame object containing data for linear regression |
weights |
weights for the model |
offset |
offsets for the model |
start |
starting values for the linear predictor |
control |
list of parameters for .control() function |
etastart |
starting values for the linear predictor |
mustart |
starting values for vector of means |
Examples
require(parallel)
data("plasma", package = "bigReg")
data_dir = tempdir()
plasma1 <- plasma
plasma1 <- data_frame(plasma1, 10, path = data_dir, nCores = 1)
plasma_glm <- bglm(ESR ~ fibrinogen + globulin, data = plasma1, family = binomial_("logit"))
summary(plasma_glm)
[Package bigReg version 0.1.5 Index]