LambertW_fit-methods: Methods for Lambert W\times F estimates

In LambertW: Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data

Methods for Lambert W\times F estimates

Description

S3 methods (print, plot, summary, etc.) for LambertW_fit class returned by the MLE_LambertW or IGMM estimators.

plot.LambertW_fit plots a (1) histogram, (2) empirical density of the data y. These are compared (3) to the theoretical F_X(x \mid \widehat{\boldsymbol \beta}) and (4) Lambert W \times F_X(y \mid \widehat{\boldsymbol \beta}) densities.

print.LambertW_fit prints only very basic information about \widehat{\theta} (to prevent an overload of data/information in the console when executing an estimator).

print.summary.LambertW_fit tries to be smart about formatting the coefficients, standard errors, etc. and also displays "significance stars" (like in the output of summary.lm).

summary.LambertW_fit computes some auxiliary results from the estimate such as standard errors, theoretical support (only for type="s"), skewness tests (only for type="hh"), etc. See print.summary.LambertW_fit for print out in the console.

Usage

## S3 method for class 'LambertW_fit'
plot(x, xlim = NULL, show.qqplot = FALSE, ...)

## S3 method for class 'LambertW_fit'
print(x, ...)

## S3 method for class 'summary.LambertW_fit'
print(x, ...)

## S3 method for class 'LambertW_fit'
summary(object, ...)

Arguments

x, object	object of class LambertW_fit
xlim	lower and upper limit of x-axis for cdf and pdf plots.
show.qqplot	should a Lambert W \times F QQ plot be displayed? Default: FALSE.
...	further arguments passed to or from other methods.

Value

summary returns a list of class summary.LambertW_fit containing

call	function call
coefmat	matrix with 4 columns: \widehat{\theta}, its standard errors, t-statistic, and two-sided p-values
distname	see Arguments
n	number of observations
data	original data (y)
input	back-transformed input data
support	support of output random variable Y
data.range	empirical data range
method	estimation method
hessian	Hessian at the optimum. Numerically obtained for method = "MLE"; for method = "IGMM" a diagonal-matrix approximation from covariance matrix obtained by simulations for n = 1000 samples in Goerg (2011).
p_m1, p_m1n	Probability that one (or n) observation were caused by input from the non-principal branch (see p_m1); only for type = "s".
symmetry.p.value	p-value from Wald test of identical left and right tail parameters (see test_symmetry); only for type = "hh".

Examples

# See ?LambertW-package

LambertW documentation built on Nov. 2, 2023, 6:17 p.m.