polio

<p>Time series of Polio incidences in U.S.A. from 1970 to 1983.</p>

datasets

Likelihood inference in Gaussian copula marginal
regression models.

Cristiano Varin

gcmr

Gaussian Copula Marginal Regression

polio function

<p>A data frame with the 168 monthly observations (from January 1970 to December 1983) with the following variables</p><table class="table">
<tr><td><code>y</code></td><td>time series of polio incidences.</td></tr>
<tr><td><code>t*10^( -3 )</code></td><td>linear trend multiplied by factor \(10^{(-3)}\).</td></tr>
<tr><td><code>cos( 2*pi*t/12 )</code></td><td>cosine annual seasonal component.</td></tr>
<tr><td><code>sin( 2*pi*t/12 )</code></td><td>sine annual seasonal component.</td></tr>
<tr><td><code>cos( 2*pi*t/6 )</code></td><td>cosine semi-annual seasonal component.</td></tr>
<tr><td><code>sin( 2*pi*t/6 )</code></td><td>sine semi-annual seasonal component.</td></tr>
</table><p></p><p></p>

Format

Polio Time Series — polio

<p>A data frame with the 168 monthly observations (from January 1970 to December 1983) with the following variables</p><table class='table'>
<tr><td><code>y</code></td><td>time series of polio incidences.</td></tr>
<tr><td><code>t*10^( -3 )</code></td><td>linear trend multiplied by factor \(10^{(-3)}\).</td></tr>
<tr><td><code>cos( 2*pi*t/12 )</code></td><td>cosine annual seasonal component.</td></tr>
<tr><td><code>sin( 2*pi*t/12 )</code></td><td>sine annual seasonal component.</td></tr>
<tr><td><code>cos( 2*pi*t/6 )</code></td><td>cosine semi-annual seasonal component.</td></tr>
<tr><td><code>sin( 2*pi*t/6 )</code></td><td>sine semi-annual seasonal component.</td></tr>
</table>



polio: Polio Time Series

Description

Usage

Arguments

Format

Examples

`y`	time series of polio incidences.
`t*10^( -3 )`	linear trend multiplied by factor \(10^{(-3)}\).
`cos( 2pit/12 )`	cosine annual seasonal component.
`sin( 2pit/12 )`	sine annual seasonal component.
`cos( 2pit/6 )`	cosine semi-annual seasonal component.
`sin( 2pit/6 )`	sine semi-annual seasonal component.