rrademacher

number of random variables to be generated

Generates Rademacher distributed random variables

Bootstrap based goodness-of-fit tests. It allows
to perform rigorous statistical tests to check if a chosen
model family is correct based on the marked empirical
process. The implemented algorithms are described in
(Dikta and Scheer (2021) <doi:10.1007/978-3-030-73480-0>)
and can be applied
to generalized linear models without any further implementation
effort. As far as certain linearity conditions are fulfilled
the resampling scheme are also applicable beyond generalized
linear models. This is reflected in the software architecture
which allows to reuse the resampling scheme by implementing
only certain interfaces for models that are not supported
natively by the package.

Marsel Scheer

bootGOF

Bootstrap Based Goodness-of-Fit Tests

Gerhard Dikta

rrademacher function

<dl><dt>n</dt>
<dd>number of random variables to be generated</dd></dl>

Arguments

Generates Rademacher distributed random variables — rrademacher

<dl>

<dt>n</dt>
<dd>number of random variables to be generated</dd>

</dl>

rrademacher: Generates Rademacher distributed random variables

Description

Usage

Value

Arguments