conditional.quantile.extremes: Plots conditional quantile plots from two datasets

In jylhaisi/post-processing-mos-point-utils: Useful functions for MOS point forecasts

Description

This function plots quantile-quantile plot from two datasets. This is an improved version from conditional.quantile() -function in "verification"-package

Usage

function(pred, obs, bins = NULL, thrs = c(10,20), main, na.rm=TRUE)

Arguments

pred	Forecasted value. ([n,1] vector, n = No. of forecasts)
obs	Observed value.([n,1] vector, n = No. of observations)
bins	Bins for forecast and observed values. A minimum number of values are required to calculate meaningful statistics. So for variables that are continuous, such as temperature, it is frequently convenient to bin these values. ([m,1] vector, m = No. of bins)
thrs	The minimum number of values in a bin required to calculate the 25th and 75th quantiles and the 10th and 90th percentiles respectively. The median+min+max values will always be displayed. ( [2,1] vector)
main	Plot title
...	plotting options

Details

add here

Value

A plot

jylhaisi/post-processing-mos-point-utils documentation built on May 20, 2019, 6:14 p.m.