Predictions in time Series Using Multivariate Regression Models
β Scribed by Frantisek Stulajter
- Book ID
- 108549464
- Publisher
- John Wiley and Sons
- Year
- 2001
- Tongue
- English
- Weight
- 158 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0143-9782
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Likelihood ratio tests for detecting a single outlier in multivariate linear models are considered, where an observation is called an outlier if there has been a shift in the mean. The test statistics are the maximum of n nonindependent statistics, where n is the number of observations. Relevant dis
Sequential procedures are proposed to estimate the regression parameters in a linear regression model with dependent residuals. The error process considered here is a linear process with unknown spectral density. The sequential point estimator for the regression parameters is based on the least-squa
## Abstract The method of ordinary least squares (OLS) and generalizations of it have been the mainstay of most forecasting methodologies for many years. It is wellβknown, however, that outliers or unusual values can have a large influence on leastβsquares estimators. Users of automatic forecasting