rpoisod

Internal function to generate random numbers following over-dispersed
Poisson distribution based on simple cheat of using a standard negative
binomial, but choosing the scale parameter to give the desired mean vs
variance ratio at the given value of the mean.
Taken from: https://stat.ethz.ch/pipermail/r-help/2002-June/022425.html

internal

Tool to assessing whether the results of a study could be influenced by
collinearity. Simulations under a given hypothesized truth regarding effects of an
exposure on the outcome are used and the resulting curves of lagged effects are
visualized. A user's manual is provided, which includes detailed examples (e.g. a
cohort study looking for windows of vulnerability to air pollution, a time series
study examining the linear association of air pollution with hospital admissions,
and a time series study examining the non-linear association between temperature and
mortality). The methods are described in Basagana and Barrera-Gomez (2021) <doi:10.1093/ije/dyab179>.

Jose Barrera-Gomez

collin

Visualization the Effects of Collinearity in Distributed Lag
Models and Other Linear Models

Xavier Basagana

rpoisod function

<dl><dt>n</dt>
<dd>integer. Number of observations.</dd>
<dt>lambda</dt>
<dd>numeric. Mean.</dd>
<dt>d</dt>
<dd>numeric. Dispersion parameter.</dd></dl>

Arguments

Internal function to generate random numbers following over-dispersed
Poisson distribution based on simple cheat of using a standard negative
binomial, but choosing the scale parameter to give the desired mean vs
variance ratio at the given value of the mean.
Taken from: https://stat.ethz.ch/pipermail/r-help/2002-June/022425.html — rpoisod

<dl>

<dt>n</dt>
<dd>integer. Number of observations.</dd>


<dt>lambda</dt>
<dd>numeric. Mean.</dd>


<dt>d</dt>
<dd>numeric. Dispersion parameter.</dd>

</dl>

Internal function to generate random numbers following over-dispersed
Poisson distribution based on simple cheat of using a standard negative
binomial, but choosing the scale parameter to give the desired mean vs
variance ratio at the given value of the mean.
Taken from: https://stat.ethz.ch/pipermail/r-help/2002-June/022425.html

Description

Usage

Value

Arguments