.fit.mslm {tidyfit}

Markov-Switching Regression for tidyfit

Description

Fits a Markov-Switching regression on a 'tidyFit' R6 class. The function can be used with regress.

Usage

## S3 method for class 'mslm'
.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)

• k (the number of regimes)

• sw (logical vector indicating which coefficients switch)

• control (additional fitting parameters)

The function provides a wrapper for MSwM::msmFit. See ?msmFit for more details.

Implementation

Note that only the regression method with 'lm' is implemented at this stage.

An argument index_col can be passed, which allows a custom index to be added to coef(m("mslm")) (e.g. a date index).

If no sw argument is passed, all coefficients are permitted to switch between regimes.“

Value

A fitted 'tidyFit' class model.

Author(s)

Johann Pfitzinger

References

Sanchez-Espigares JA, Lopez-Moreno A (2021). MSwM: Fitting Markov Switching Models. R package version 1.5, https://CRAN.R-project.org/package=MSwM.

See Also

.fit.tvp and m methods

Examples

# Load data
data <- tidyfit::Factor_Industry_Returns
data <- dplyr::filter(data, Industry == "HiTec", Date >= 201801)
data <- dplyr::select(data, -Industry)

ctr <- list(maxiter = 100, parallelization = FALSE)

# Stand-alone function
fit <- m("mslm", Return ~ HML, data, index_col = "Date", k = 2, control = ctr)
fit

# Within 'regress' function
fit <- regress(data, Return ~ HML,
               m("mslm", index_col = "Date", k = 2, control = ctr))
tidyr::unnest(coef(fit), model_info)