Chi-Square Test in Time Series Data
Kelechukwu C. N. Dozie, Stephen O. Ihekuna
Asian Journal of Probability and Statistics · pp. 49–63 · Published 19 Oct 2022
10.9734/ajpas/2022/v20i3426Abstract
This study examines the application of Chi-Square test in time series data which considers the mixed model structure and linear trending curve. The Chi-Square test is applied to the seasonal variances of the Buys-Ballot table. The emphasis is to assess the validity of the Chi-Square test using empirical examples. One hundred simulated numerical examples are used to illustrate the applicability of the Chi-Square test. Using empirical example, the Chi-Square test successfully recorded 100% of times for the mixed model. This expresses a high degree of confidence in the Chi-Square test.
References (9)
- 1 The Analysis of Time Series: An Introduction. [DOI]
- 2 Uses of the Buys-Ballot Table in Time Series Analysis [DOI]
- 3 A Comparative Study on Additive and Mixed Models in Descriptive Time Series [DOI]
- 4 Choice between Mixed and Multiplicative Models in Time Series Decomposition
- 5 Procedure for Estimation of Additive Time Series Model [DOI]
- 6 Road Traffic Offences in Nigeria: An Empirical Analysis using Buys-Ballot Approach [DOI]
- 7 Additive Seasonality in Time Series using Row and Overall Sample Variances of the Buys-Ballot Table [DOI]
- 8 Buys-Ballot Estimates for Mixed Model in Descriptive Time Series
- 9 The Analysis of Mixed Model in Time Series Decomposition
Cited by 4
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Kelechukwu C. N. Dozie, Christian Chinwe Ibebuogu · Asian Journal of Probability and Statistics · 2023
Kelechukwu C. N. Dozie, Christian Chinwe Ibebuogu · Asian Journal of Probability and Statistics · 2023
Showing 3 of 4 known citations — external sources report more than can currently be individually listed.
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