normalizeGaussian {RMAWGEN} | R Documentation |
Converts a random variable x
extracted by a population represented by the sample data
or sample
to a normally-distributed variable with assigned mean and standard deviation or vice versa in case inverse
is TRUE
Description
Converts a random variable x
extracted by a population represented by the sample data
or sample
to a normally-distributed variable with assigned mean and standard deviation or vice versa in case inverse
is TRUE
Usage
normalizeGaussian(x = 0, data = x, cpf = NULL, mean = 0, sd = 1,
inverse = FALSE, step = NULL, prec = 10^-4, type = 3,
extremes = TRUE, sample = NULL)
Arguments
x |
value or vector of values to be converted |
data |
a sample of data on which a non-parametric probability distribution is estimated |
cpf |
cumulative probability distribution. If |
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 |
step |
vector of values in which step discontinuities of the cumulative probability function occur. Default is |
prec |
amplitude of the neighbourhood of the step discontinuities where cumulative probability function is treated as non-continuous. |
type |
see |
extremes |
logical variable.
If
where |
sample |
a character string or |
Value
the normalized variable or its inverse
@note This function makes a Marginal Gaussianization. See the R code for further details
Author(s)
Emanuele Cordano, Emanuele Eccel