RPS One-off Predictions

Data:
Fit From:
Fit Number :
Predict Number :
Number Ahead:
Model:
Fit, predict, and evaluate example showing many features of TimeSeries

The input file should be a one (value) or two column (timestamp value) ascii file The model is fit from offset "Fit from" to "Fit from + Fit number -1 ". Predictions are made from "Fit from + Fit Number" to "Fit From + Fit Number + Predict Number - 1". At each of these samples, "Number Ahead" predictions are made. The model used is as follows:

A Model is in the form [optional modifier] [required underlying model]

Optional Modifiers That Affect Predictors Produced From the Underlying Model
----------------------------------------------------------------------------
REFIT r
 predictor will refit itself every r data elements
AWAIT a
 predictor will wait for a data elements before fitting
MANAGED a r m e v
 predictor will wait for a data elements before fitting
 predictor will refit after r data elements
 predictor will refit if, after m samples, the relative error of one-step
  ahead predictions exceeds e (avg(abs(obs-pred)/abs(pred)) > e)
 predictor will refit if, after m samples, the actual error variance of
  one-step ahead predictions exceeds their predicted variance by 
  a factor of v (variance(error)/predictedvariance > v)

Underlying Models
-----------------
NONE
 No model
MEAN
 Long-term mean
LAST
 Last value seen
BM p | BESTMEAN p
 Windowed average, window length chosen to minimize msqerr
BMED p | BESTMEDIAN p
 Windowed median, window length chosen to minimize msqerr
AR p
 Autoregressive model of order p
MA q
 Moving average model of order q
ARMA p q
 Autoregressive moving average model of order p+q
ARIMA p d q
 Autoregressive integrated moving average model of order p+q with
  d-order difference
ARFIMA p d q
 Fractionally integrated ARIMA model of order p+q.  d is ignored and
  and determined by the model fitting process

RPS: Resource Prediction System Toolkit

Copyright (c) 1999-2002 by Peter A. Dinda
Use subject to license.

http://www.cs.northwestern.edu/~RPS
rps-help@cs.northwestern.edu