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

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

See Also

normalizeGaussian

Examples

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)


 

RMAWGEN documentation built on May 29, 2017, 9:09 a.m.