broom (version 0.4.1)

biglm_tidiers: Tidiers for biglm and bigglm object

Description

Tidiers for biglm object from the "biglm" package, which contains a linear model object that is limited in memory usage. Generally the behavior is as similar to the lm_tidiers as is possible. Currently no augment is defined.

Usage

"tidy"(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, quick = FALSE, ...)
"glance"(x, ...)

Arguments

x
a "biglm" object
conf.int
whether to include a confidence interval
conf.level
confidence level of the interval, used only if conf.int=TRUE
exponentiate
whether to exponentiate the coefficient estimates and confidence intervals (typical for logistic regression)
quick
whether to compute a smaller and faster version, containing only the term and estimate columns.
...
extra arguments (not used)

Value

All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.tidy.biglm returns one row for each coefficient, with columns
term
The term in the linear model being estimated and tested
estimate
The estimated coefficient
std.error
The standard error from the linear model
p.value
two-sided p-value
If conf.int=TRUE, it also includes columns for conf.low and conf.high, computed with confint.glance.biglm returns a one-row data frame, with columns
r.squared
The percent of variance explained by the model
AIC
the Akaike Information Criterion
deviance
deviance
df.residual
residual degrees of freedom

Examples

Run this code

if (require("biglm", quietly = TRUE)) {
    bfit <- biglm(mpg ~ wt + disp, mtcars)
    tidy(bfit)
    tidy(bfit, conf.int = TRUE)
    tidy(bfit, conf.int = TRUE, conf.level = .9)
    
    glance(bfit)
    
    # bigglm: logistic regression
    bgfit <- bigglm(am ~ mpg, mtcars, family = binomial())
    tidy(bgfit)
    tidy(bgfit, exponentiate = TRUE)
    tidy(bgfit, conf.int = TRUE)
    tidy(bgfit, conf.int = TRUE, conf.level = .9)
    tidy(bgfit, conf.int = TRUE, conf.level = .9, exponentiate = TRUE)
    
    glance(bgfit)
}

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