FcGeneralizedLinearModels4TS: Forecasting with Generalized Linear Models for time series

In Mthrun/TSAT: Time Series Analysis Tools (TSAT)

Forecasting with Generalized Linear Models for time series

Description

Generalized linear models for the forecast of time series in the multivariate case

Usage

FcGeneralizedLinearModels4TS(Response, SplitAt, Predictor1, Predictor2 = NULL, 

CorrectionFactor=FALSE, PlotIt = TRUE,Time, Summary = FALSE,...)

Arguments

Response	[1:n] vector with an value of each time j in [1,n]
SplitAt	scalar 'k' with k<n, index of row where the DataFrame is divided into test and train data
Predictor1	[1:n] vector with an value of each time j in [1,n]
Predictor2	[1:n] vector with an value of each time j in [1,n]. Can also be NULL if not used
Time	Optional, [1:n] time vector in case of PlotIt=TRUE
CorrectionFactor	Scalar, if TRUE: the predicted time series will begin at the same point as the last value of the training set. All other values will be mulitplied by a factor accordingly.
PlotIt	Optional,FALSE (default), do nothing. TRUE: plots an evaluation of the forecast on the test data FALSE: Plots data model and prediction with
Summary	Output of glm is evaluated further
...	Further arguments passed to glm

Details

Assumption: Response and 'Predictors' have the same time intervals, the same starting time and the same length.

Value

list with

Forecast	[k:n], the forecast, of the time interval [k,n] which was not used in the model
TestSet	[k:n], the part of Response not used in the model
Accuracy	ME, RMSE, MAE, MPE, MAPE of training and test dataset in a matrix
Errors	Residuals: TestSet-Forecast
Model	Output of glm

Note

Wrapper for glm with some additional features

Author(s)

Michael Thrun

Mthrun/TSAT documentation built on Feb. 5, 2024, 11:15 p.m.