season-package: Tools for uncovering and estimating seasonal patterns.

In season: Seasonal analysis of health data

Description

The package contains graphical methods for displaying seasonal data and regression models for detecting and estimating seasonal patterns.

The regression models can be applied to normal, Poisson or binomial dependent data distributions. Tools are available for both time series data (equally spaced in time) and survey data (unequally spaced in time).

Sinusoidal (parametric) seasonal patterns are available (cosinor, nscosinor), as well as models for monthly data (monthglm), and the case-crossover method to control for seasonality (casecross).

Details

season aims to fill an important gap in the R software by providing a range of tools for analysing seasonal data. The examples are based on health data, but the functions are equally applicable to any data with a seasonal pattern.

In the next version we hope to make the nscosinor function faster and improve the plots.

Package:	season
Type:	Package
Version:	0.2-6
Date:	2011-10-23
License:	GPL (>= 3)

Author(s)

Adrian Barnett <a.barnett<at>qut.edu.au>
Peter Baker <p.baker1<at>uq.edu.au>

Maintainer: Adrian Barnett <a.barnett<at>qut.edu.au>

References

Barnett, A.G., Dobson, A.J. (2010) Analysing Seasonal Health Data. Springer.

Examples

## see examples for \code{\link{cosinor}}, \code{\link{monthglm}},
##                  \code{\link{nscosinor}} and \code{\link{casecross}}

Example output

Loading required package: ggplot2
Loading required package: MASS
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-20. For overview type 'help("mgcv-package")'.
Loading required package: survival
Loading required package: coda

season documentation built on May 2, 2019, 5:22 p.m.