dot-fit.blasso: Bayesian Lasso regression for 'tidyfit'

In tidyfit: Regularized Linear Modeling with Tidy Data

Bayesian Lasso regression for tidyfit

Description

Fits a Bayesian Lasso regression on a 'tidyFit' R6 class. The function can be used with regress.

Usage

## S3 method for class 'blasso'
.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 monomvn::blasso. See ?blasso for more details.

Implementation

Features are standardized by default with coefficients transformed to the original scale.

Value

A fitted tidyFit class model.

Author(s)

Johann Pfitzinger

References

Gramacy RB, (qpgen2/quadprog) wFcfCMaubBAT (2023). monomvn: Estimation for MVN and Student-t Data with Monotone Missingness. R package version 1.9-17, https://CRAN.R-project.org/package=monomvn.

See Also

.fit.lasso, .fit.bridge and m methods

Examples

# Load data
data <- tidyfit::Factor_Industry_Returns

# Stand-alone function
fit <- m("blasso", Return ~ ., data, T = 100)
fit

# Within 'regress' function
fit <- regress(data, Return ~ ., m("blasso", T = 100),
               .mask = c("Date", "Industry"))
coef(fit)

tidyfit documentation built on April 4, 2025, 4:38 a.m.