Previously we’ve covered the basics of exogenous variables in smooth functions. Today we will go slightly crazy and discuss automatic variables selection. But before we do that, we need to look at a Santa’s little helper function implemented in smooth. It is called xregExpander(). It is useful in cases when you think that your exogenous […]

# Common parameters

Posts about the parameters that are common across the forecasting functions of smooth package

# “smooth” package for R. Common ground. Part III. Exogenous variables. Basic stuff

One of the features of the functions in smooth package is the ability to use exogenous (aka “external”) variables. This potentially leads to the increase in the forecasting accuracy (given that you have a good estimate of the future exogenous variable). For example, in retail this can be a binary variable for promotions and we […]

# “smooth” package for R. Common ground. Part II. Estimators

UPDATE: Starting from the v2.5.1 the cfType parameter has been renamed into loss. This post has been updated since then in order to include the more recent name. A bit about estimates of parameters Hi everyone! Today I want to tell you about parameters estimation of smooth functions. But before going into details, there are […]

# “smooth” package for R. Common ground. Part I. Prediction intervals

UPDATE: Starting from v2.5.1 the parameter intervals has been renamed into interval for the consistency purposes with the other R functions. We have spent previous six posts discussing basics of es() function (underlying models and their implementation). Now it is time to move forward. Starting from this post we will discuss common parameters, shared by […]