FlashAustriaModel {FlashAustria}R Documentation

Fitted Distributional Regression Model Object (bamlss)

Description

A zero-truncated negative binomial bamlss model trained on the FlashAustriaTrain data using gradient boosting with subsequent MCMC sampling. The response variable are the lightning counts and the regression terms are P-splines based on ERA5 covariates.

Format

An object of class bamlss.

References

Umlauf, N., Klein, N., and Zeileis, A. (2018). BAMLSS: Bayesian Additive Models for Location, Scale and Shape (and Beyond). Journal of Computational and Graphical Statistics, 27(3), 612–627. doi: 10.1080/10618600.2017.1407325

Examples

## Visualization of fitted model
if(require("bamlss")) {
data("FlashAustriaModel", package = "FlashAustria")
plot(FlashAustriaModel)
}

## Replication code:
## Not run: 
## Learning data
data("FlashAustria", package = "FlashAustria")

## Model formula
f <- list(
  counts ~ s(d2m, bs = "ps") + s(q_prof_PC1, bs = "ps") +
    s(cswc_prof_PC4, bs = "ps") + s(t_prof_PC1, bs = "ps") +
    s(v_prof_PC2, bs = "ps") + s(sqrt_cape, bs = "ps"), 
  theta ~ s(sqrt_lsp, bs = "ps")
)

## Model fitting using boosting with subsequent MCMC sampling
set.seed(111)
FlashAustriaModel <- bamlss(f,
  family = "ztnbinom", data = FlashAustriaTrain,
  optimizer = boost, maxit = 1000,
  thin = 5, burnin = 1000, n.iter = 6000)

## End(Not run)

[Package FlashAustria version 0.3-0 Index]