FlashAustriaModel {FlashAustria} | R Documentation |
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.
An object of class bamlss
.
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
## 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)