XFcstTrue: Forecast for covariate matrix: using true generating process

In yymmhaha/PackPaper1: Package related to my first paper

Description

Forecast using the true X process specified, depending on the data type (uncorrelated, correlated).

It is the noise-free 'forecaster', and part of XintvCorr or XintvSimple for intervention. (??)

Usage

XFcstTrue(datatype, horizon, parameters.of.X, Xinput)

Arguments

datatype	a string. Choose from 'simple', 'block1', 'block2'.
horizon	a number. Forecast horizon.
parameters.of.X	a list. The one that has been used for simulation.
Xinput	a matrix. The original training X matrix for forecast, DAT$X.for.fcst (10 series)

Details

This function (including the simple, and 2 correlated) are essentially the "no intervention" part of the intervention using true process - since I have produced those functions first, this one is to set the baseline for forecasting because in reality it's impossible to know the true process. In another word, this is the best forecast can be achieved ever.

Value

a matrix

xtrue.fcst

a matrix. Forecast values for each series produced by true method.

Examples

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yymmhaha/PackPaper1 documentation built on May 24, 2019, 8:55 a.m.