Generalized linear mixed-effects model for tidyfit

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).

Value

A fitted 'tidyFit' class model.

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

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.

Author

Johann Pfitzinger

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
#> # A tibble: 1 × 7
#>   model estimator_fct `size (MB)` grid_id  model_object settings messages 
#>   <chr> <chr>               <dbl> <chr>    <list>       <list>   <chr>    
#> 1 logit lme4::glmer          1.31 #0010000 <tidyFit>    <tibble> "boundar…

Generalized linear mixed-effects model for `tidyfit`