cocoResid

Calculates the (Pearson) residuals of a fitted model for model evaluation purposes.

Useful tools for fitting, validating, and forecasting of practical convolution-closed time series models for low counts are provided. Marginal distributions of the data can be modelled via Poisson and Generalized Poisson innovations. Regression effects can be incorporated through time varying innovation rates. The models are described in Jung and Tremayne (2011) <doi:10.1111/j.1467-9892.2010.00697.x> and the model assessment tools are presented in Czado et al. (2009) <doi:10.1111/j.1541-0420.2009.01191.x> and, Tsay (1992) <doi:10.2307/2347612>.

Manuel Huth

coconots

Convolution-Closed Models for Count Time Series

Robert C. Jung

Andy Tremayne

cocoResid function

<dl><dt>coco</dt>
<dd>An object of class "coco</dd>
<dt>val.num</dt>
<dd>A non-negative real number that halts the calculation once the cumulative probability reaches 1-<code>val.num</code></dd></dl>

Arguments

Author

Residual Based Model Assessment Procedure — cocoResid

<dl>

<dt>coco</dt>
<dd>An object of class "coco</dd>


<dt>val.num</dt>
<dd>A non-negative real number that halts the calculation once the cumulative probability reaches 1-<code>val.num</code></dd>

</dl>

cocoResid: Residual Based Model Assessment Procedure

Description

Usage

Value

Arguments

Author

Details