TMEV prediction — predict.mevr • mevr

Takes a mevr object where the TMEV has been fitted to rainfall data and calculates bamlss predictions for the distributional parameters and the model terms. Basically a wrapper to the corresponding function predict.bamlss

Usage

# S3 method for class 'mevr'
predict(object, newdata, term, ...)

Arguments

object: Object of class mevr, fitted with the TMEV.
newdata: A data frame with the model covariates (year, yday) at which predictions are required. Note that depending on argument term, only covariates that are needed by the corresponding model terms need to be supplied. If not supplied, predictions are made on the data supplied by the fitted object x.
term: Character of the model terms for which predictions shall be calculated. Can only be "year" or "yday". If not specified, predictions for all terms are calculated.
...: Arguments passed to prediction functions that are part of a bamlss.family object, i.e., the objects has a $predict() function that should be used instead.

Value

A data.frame with the supplied covariables and the predicted parameters.

Details

See also the details of ftmev for an explanation of the model terms used to fit the temporal trend of the Weibull parameters. The basis dimensions yday_ti_shape_k, yday_ti_scale_k, year_ti_shape_k, year_ti_scale_k are taken from the fitting process, i.e. the call to ftmev.

Examples

data(dailyrainfall)

# restrict for the sake of speed
idx <- which(as.POSIXlt(dailyrainfall$date)$year + 1900 < 1976)
data <- dailyrainfall[idx, ]

f <- ftmev(data, minyears = 5)
predict(f, term = "year")
#>   year c.pred.year w.pred.year
#> 1 1971    79.87684   0.8607488
#> 2 1972    83.21258   0.8772784
#> 3 1973    86.68762   0.8941253
#> 4 1974    90.30778   0.9112958
#> 5 1975    94.07913   0.9287961