ESTIMATION AND TESTING OF A MULTIVARIATE EXPONENTIAL SMOOTHING MODEL
- 1 March 1990
- journal article
- Published by Wiley in Journal of Time Series Analysis
- Vol. 11 (2) , 89-105
- https://doi.org/10.1111/j.1467-9892.1990.tb00044.x
Abstract
The form of the spectral likelihood function of a multivariate stochastic process permits straightforward construction of a scoring algorithm for maximum likelihood estimation using first derivatives only and a score test statistic for hypothesis testing. These techniques are applied to the analysis of a multivariate exponential smoothing model for which the homogeneity hypothesis is also discussed.Keywords
This publication has 23 references indexed in Scilit:
- Model Specification Tests Based on Artificial Linear RegressionsInternational Economic Review, 1984
- Maximum Likelihood Estimation of Regression Models with First Order Moving Average Errors when the Root Lies on the Unit CircleEconometrica, 1983
- Analyzing Permanent and Transient Influences in Multiple Time Series ModelsJournal of Business & Economic Statistics, 1983
- A One-Factor Multivariate Time Series Model of Metropolitan Wage RatesJournal of the American Statistical Association, 1981
- The efficient estimation of vector linear time series modelsBiometrika, 1976
- Vector linear time series modelsAdvances in Applied Probability, 1976
- Omnibus Test Contours for Departures from Normality Based on √b 1 and b 2Biometrika, 1975
- Distribution of Residual Autocorrelations in Multiple Autoregressive SchemesJournal of the American Statistical Association, 1974
- Distribution of Residual Autocorrelations in Multiple Autoregressive SchemesJournal of the American Statistical Association, 1974
- The estimation of mixed moving average autoregressive systemsBiometrika, 1969