Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
A New Bayesian Formulation for Holt's Exponential Smoothing
 

Summary: A New Bayesian Formulation for Holt's
Exponential Smoothing
ROBERT R. ANDRAWIS1
* AND AMIR F. ATIYA2
1
Data Mining Center of Excellence, MCIT, Cairo, Egypt
2
Department of Computer Engineering, Cairo University, Giza,
Egypt
ABSTRACT
In this paper we propose a Bayesian forecasting approach for Holt's additive
exponential smoothing method. Starting from the state space formulation, a
formula for the forecast is derived and reduced to a two-dimensional integration
that can be computed numerically in a straightforward way. In contrast to much
of the work for exponential smoothing, this method produces the forecast
density and, in addition, it considers the initial level and initial trend as part of
the parameters to be evaluated. Another contribution of this paper is that we
have derived a way to reduce the computation of the maximum likelihood
parameter estimation procedure to that of evaluating a two-dimensional grid,
rather than applying a five-variable optimization procedure. Simulation exper-

  

Source: Atiya, Amir - Computer Engineering Department, Cairo University

 

Collections: Computer Technologies and Information Sciences