dot-fit.glmm: Generalized linear mixed-effects model for 'tidyfit'

In tidyfit: Regularized Linear Modeling with Tidy Data

Generalized linear mixed-effects model for tidyfit

Description

Fits a linear or logistic mixed-effects model (GLMM) on a 'tidyFit' R6 class. The function can be used with regress and classify.

Usage

## S3 method for class 'glmm'
.fit(self, data = NULL)

Arguments

self	a 'tidyFit' R6 class.
data	a data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr).

Details

Hyperparameters:

None. Cross validation not applicable.

Important method arguments (passed to m)

The function provides a wrapper for lme4::glmer. See ?glmer for more details.

Implementation

No implementation notes

Value

A fitted 'tidyFit' class model.

Author(s)

Johann Pfitzinger

References

Douglas Bates, Martin Maechler, Ben Bolker, Steve Walker (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48. doi:10.18637/jss.v067.i01.

See Also

.fit.glm and m methods

Examples

# Load data
data <- tidyfit::Factor_Industry_Returns
data$Return <- ifelse(data$Return > 0, 1, 0)

# Estimate model with random effects
fit <- classify(data, Return ~ CMA + (CMA | Industry), logit = m("glmm"),
                .mask = "Date")
fit

tidyfit documentation built on Oct. 3, 2024, 5:06 p.m.