Recipes for creating state-space models in R
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LICENSE Initial commit Jul 16, 2015
README.md
localLevel-dlm.R
localLevel.R First-cut at R code Jul 17, 2015
localLinearTrend-dlm.R
localLinearTrend.R
randomWalk-dlm.R
randomWalk.R
regressionFixedCoeffs.R First-cut at R code Jul 17, 2015
regressionMultiVariate.R
regressionVaryingCoeffs.R First-cut at R code Jul 17, 2015

README.md

Recipes for State-Space Models in R

State-space models are useful for modeling time series data, and R contains several excellent packages for creating the models. Unfortunately, using these packages involves many little details, and I can never remember them. So I put together some recipes to let me quickly build state-space models.

I describe the recipes on my website.

http://www.quantdevel.com/public/StateSpaceModels/

This repository contains R code for the recipes. These are the main recipes, most likely to be useful for day-to-day work:

  • localLevel.R - Local level model
  • localLinearTrend.R - Local linear trend model
  • regressionFixedCoeffs.R - Regression model with fixed coefficients
  • regressionVaryingCoeffs.R - Regression model with time-varying coefficients

These recipes may come in handy in special circumstances:

  • randomWalk.R - Random walk model, StructTS implementation
  • randomWalk-dlm.R - Random walk model, dlm implemenation
  • localLevel-dlm.R - Local level model, dlm implemenatation
  • localLinearTrend-dlm.R - Local linear trend model, dlm implementation