# normalizeGaussian_severalstations: Converts several samples 'x' random variable extracted by... In RMAWGEN: Multi-Site Auto-Regressive Weather GENerator

## Description

Converts several samples x random variable extracted by populations represented by the columns of data respectively or sample to a normally-distributed samples with assinged mean and standard deviation or vice versa in case inverse is TRUE

## Usage

 1 2 3 normalizeGaussian_severalstations(x, data = x, cpf = NULL, mean = 0, sd = 1, inverse = FALSE, step = NULL, prec = 10^-4, type = 3, extremes = TRUE, sample = NULL, origin_x = NULL, origin_data = NULL) 

## Arguments

 x value to be converted data a sample of data on which a non-parametric probability distribution is estimated cpf cumulative probability distribution. If NULL (default) is calculated as ecdf(data) mean mean (expected value) of the normalized random variable. Default is 0. sd standard deviation of the normalized random variable. Default is 1. inverse logical value. If TRUE the function works inversely (the opposite way). Default is FALSE. step vector of values in which step discontinuities of the cumulative probability function occur. Default is NULL prec amplitude of the neighbourhood of the step discontinuities where cumulative probability function is treated as non-continuous. type see quantile extremes logical variable. If TRUE (default) the probability or frequency is multiplied by \frac{N}{N+1} where N is the length of data sample information on how to sample x and data. Default is NULL, this means that the values of each column of x and data belong to the same sample. If x and data are sampled for each month seperately, it is set to monthly. origin_x date corresponding to the first row of x origin_data date corresponding to the first row of data

## Value

a matrix with the normalized variable or its inverse

## Note

It applies normalizeGaussian for each column of x and data. See the R code for further details

## Author(s)

Emanuele Cordano, Emanuele Eccel

normalizeGaussian
  1 2 3 4 5 6 7 8 9 10 11 12 library(RMAWGEN) N <- 30 x <- rexp(N) y <- x+rnorm(N) df <- data.frame(x=x,y=y) dfg <- normalizeGaussian_severalstations(df,data=df,extremes=TRUE,inverse=FALSE) dfi <- normalizeGaussian_severalstations(dfg,data=df,extremes=TRUE,inverse=TRUE)