Basic Properties of Buys-ballot Seasonal Variances Estimates for Choice of Models in Time Series
Kelechukwu C. N. Dozie, Christian C. Ibebuogu
Asian Journal of Advanced Research and Reports · pp. 19–29 · Published 31 Jan 2023
10.9734/ajarr/2023/v17i2466Abstract
This article presents basic properties of Buys-Ballot estimates for seasonal variances for the mixed, multiplicative and additive models in time series. The emphasis is to characterize the basic properties of seasonal variances for purpose of choice of model. In this article, the method of seasonal variances with illustrative examples for choice of suitable models in time series decomposition is also considered. Results show that, seasonal variances of the Buys-Ballot estimates are for additive model 1) a product of trending parameter only 2) It is a product season j through the square of the seasonal indices s2j and parameters through the square of the seasonal averages X-2.j for multiplicative model 3) A constant multiple of the square of the seasonal indices s2j for mixed model.
Cited by 0
No indexed citations yet.
Related research
- Estimation of Seasonal Variances in Descriptive Time Series Analysis — shares topic coverage
- A Comparative Study of Detrending Methods on Crop Yield Time Series for Drought Studies — shares topic coverage
- Buys-Ballot Estimates for Overall Sample Variances and Their Statistical Properties: A Mixed Model Case — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
0
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.