gamma_01 {LambertW} | R Documentation |
Input parameters to get a zero mean, unit variance output for a given gamma
Description
Computes the input mean \mu_x(\gamma)
and standard deviation
\sigma_x(\gamma)
for input X \sim F(x \mid \boldsymbol \beta)
such that the resulting skewed Lambert W x F RV Y
with
\gamma
has zero-mean and unit-variance. So far works only for Gaussian
input and scalar \gamma
.
The function works for any output mean and standard deviation, but
\mu_y = 0
and \sigma_y = 1
are set as default as they
are the most useful, e.g., to generate a standardized Lambert W white noise
sequence.
Usage
gamma_01(gamma, mu.y = 0, sigma.y = 1, distname = "normal")
Arguments
gamma |
skewness parameter |
mu.y |
output mean; default: |
sigma.y |
output standard deviation; default: |
distname |
string; name of distribution. Currently only supports |
Value
A 5-dimensional vector (\mu_x(\gamma)
, \sigma_x(\gamma)
, \gamma
, 0, 1),
where \delta = 0
and \alpha = 1
are set for the sake of compatiblity with
other functions.
Examples
gamma_01(0) # for gamma = 0, input == output, therefore (0,1,0,0,1)
# input mean must be slightly negative to get a zero-mean output
gamma_01(0.1) # gamma = 0.1 means it is positively skewed
gamma_01(1)