Numerical Prediction Software System

A Numerical Prediction Software System is a prediction system that solves a numerical prediction task by implementing a numerical prediction algorithm.

• AKA: Point Estimation Software.
• Context:
  • It can (typically) require the use of a Sorting Algorithm.
  • It can range from being a Heuristic Point Estimation System to being a Data-Driven Point Estimation System (e.g. a supervised point estimation system).
• Example(s):
  • a Time Series Point Estimation System.
  • an IID Point Estimation System, such as: pointStats.pl, pointStats.py, pointStats.R, and GM-RKB.PointStats.java.
  • an MLE-based System.
  • …
• Counter-Example(s):
  • an Interval Estimation System.
  • an OLAP System.
  • a Class Prediction System.
• See: Machine Learning System, Exploratory Analysis System.

---

---

References

2008

• (Hyndman & Khandakar, 2008) ⇒ Rob J Hyndman, and Yeasmin Khandakar. (2008). “Automatic time series forecasting: the forecast package for R.” In: Journal of Statistical Software, 27(3).
  • ABSTRACT: Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models that underly exponential smoothing methods. The second is a step-wise algorithm for forecasting with ARIMA models. The algorithms are applicable to both seasonal and non-seasonal data, and are compared and illustrated using four real time series. We also briefly describe some of the other functionality available in the forecast package.

---