Description Usage Arguments Value Note Author(s) See Also Examples
View source: R/normalizeGaussian_sevaralstations.R
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
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x |
value 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 \frac{N}{N+1} where N is the length of |
sample |
information on how to sample |
origin_x |
date corresponding to the first row of |
origin_data |
date corresponding to the first row of |
a matrix with the normalized variable or its inverse
It applies normalizeGaussian
for each column of x
and data
.
See the R code for further details
Emanuele Cordano, Emanuele Eccel
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