scholarly journals INSTALLING ENERGY MONITORING SYSTEM FOR CONSUMER SECTOR IN INDONESIA AND ENERGY USE PREDICTION BY MULTIPLE-TIME SERIES MODELLING

2017 ◽  
Vol 73 (6) ◽  
pp. II_35-II_43 ◽  
Author(s):  
Seiya MAKI ◽  
Shuichi ASHINA ◽  
Minoru FUJII ◽  
Kenji UCHIDA ◽  
Kengo AIZAWA ◽  
...  
Keyword(s):  
Time Series ◽  
Monitoring System ◽  
Energy Use ◽  
Multiple Time ◽  
Multiple Time Series ◽  
Energy Monitoring ◽  
Time Series Modelling ◽  
Energy Use Prediction

Robust multiple time series modelling

Biometrika ◽  
1989 ◽  
Vol 76 (2) ◽  
pp. 309-315 ◽  
Author(s):  
W. K. LI ◽  
Y. V. HUI
Keyword(s):  
Time Series ◽  
Multiple Time ◽  
Multiple Time Series ◽  
Time Series Modelling

Stochastic Investment Modelling: a Multiple Time-Series Approach

2002 ◽  
Vol 8 (3) ◽  
pp. 545-591 ◽  
Author(s):  
W.S. Chan
Keyword(s):  
Time Series ◽  
Interest Rates ◽  
A Priori ◽  
Investment Model ◽  
Multiple Time ◽  
Multiple Time Series ◽  
Price Inflation ◽  
Diagnostic Checking ◽  
Time Series Modelling ◽  
Time Series Approach

ASBTRACTIn this paper we adopt the multiple time-series modelling approach suggested by Tiao & Box (1981) to construct a stochastic investment model for price inflation, share dividends, share dividend yields and long-term interest rates in the United Kingdom. This method has the advantage of being direct and transparent. The sequential and iterative steps of tentative specification, estimation and diagnostic checking parallel those of the well-known Box-Jenkins method in the univariate time-series analysis. It is not required to specify any a priori causality as compared to some other stochastic asset models in the literature.

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