downloads

<p>The data represent the number of daily downloads of a TeX-editor between
June 2006 and February 2007. The dataset contains 267 observations.
The data have been provided by Christian Weiss.</p>

datasets

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

downloads function

<p>A time series (<code>ts</code>) object containing daily data from June 2006 to February 2007.</p>

downloads: Time Series of Daily Downloads of a TeX-Editor

Description

Usage

Arguments

Format