get_Sliding_Indexes​(numRecords, windowLag, predHorizon, windowPattern, stepSize)

Generates sliding window indexes for auto regression on a univariate time series

Useful for autoregression on a univariate time series.
Returns the indexes for the predictor and response variables according to a sliding window.
Parameters:
numRecords - the number of records in the dataset

windowLag - number of past samples to take - it will be equal to
the size of the predictor vector X. Default 10

predHorizon - the prediction horizon is the number of steps into
the future that predictions are to be made. Default 1

windowPattern - by default the window will take all consecutive
values in the past over the window lag size, however it is
possible to sample using a custom pattern.
For example taking every second value can be done by setting
this parameter to 1:2:5. Default 1:windowLag

stepSize - number of steps taken when window is moved. Default 1

Returns:
indX - predictor variable indexes
indY - response variable indexes