FAmle-internal: Internal Functions in the FAmle Package

In FAmle: Maximum Likelihood and Bayesian Estimation of Univariate Probability Distributions

Internal Functions in the FAmle Package

Description

Internal functions in the FAmle package .

Usage

cdf.plot(z)
delta.Q(p, model, ln = FALSE)
delta.QQ(model, alpha = 0.1, ln = FALSE)
Diff.1(x, f, h = 1e-04)
Diff.2(k, i, model, p, ln = FALSE)
Diff.3(i, model, p, ln = FALSE)
## S3 method for class 'metropolis'
hist(x, density = TRUE, ...)
## S3 method for class 'plot'
hist(x,...)
Plot.post.pred(x, ...)
post.pred(z, fun = NULL)
Quantile.plot(z, ci = FALSE, alpha = 0.05)
Return.plot(model, ci = FALSE, alpha = 0.05)
Carlin(x)

Arguments

z	A mle object.
p	A vector of probabilities.
model	A mle object.
ln	Whether or not (TRUE or FALSE) computations should be carried out on the natural logarithmic scale.
alpha	The significance level.
x	Value at which the numerical derivative should be evaluated. For the Carlin function (see References for metropolis), this x corresponds to an object from the class metropolis.
f	A function to be differentiated.
h	Small number representing a small change in x.
k	Parameter value at which the first derivative should be evaluated.
i	Position of the parameter, within a vector of parameters, with respect to which differentiation should be carried out.
density	Whether or not (TRUE or FALSE) a Kernel density should be added to the histogram - see density.
...	Additional arguments pertaining to hist.
fun	optional argument that may be used to modify the scale on which the histogram will be plotted.
ci	Whether or not (TRUE or FALSE) approximated 100*(1-alpha) confidence intervals should be added to the plot (either Quantile.plot or Return.plot).

FAmle documentation built on March 18, 2022, 5:29 p.m.