trend: Bias With Linear Time Trend

In jonasbhend/biascorrection: Bias Correct Ensemble Forecasts

Bias With Linear Time Trend

Description

Computes mean de-biasing with linear time trend

Usage

trend(...)

trendRecal(...)

Arguments

...	arguments passed to linmod

Details

This bias correction method assumes that the bias can be decomposed into a stationary seasonal cycle (as in method smoothobs) and a linear time trend estimated from the residuals.

See Also

linmod

Examples

## initialise forcast observation pairs
fcst <- array(rnorm(215*30*51), c(215, 30, 51)) + 
0.5*sin(seq(0,4,length=215)) + 
rep(seq(0,1,length=30), each=215)
obs <- array(rnorm(215*30, mean=2), c(215, 30)) + 
sin(seq(0,4, length=215)) + 
rep(seq(0,3,length=30), each=215)
fc.time <- outer(1:215, 1981:2010, function(x,y) as.Date(paste0(y, '-11-01')) - 1 + x)
fcst.debias <- biascorrection:::trend(fcst[,1:20,], 
obs[,1:20], fcst.out=fcst, fc.time=fc.time[,1:20], fcout.time=fc.time, span=0.5)

jonasbhend/biascorrection documentation built on Nov. 11, 2023, 1:16 a.m.