Research Paper
Year: 2020 | Month: June | Volume: 7 | Issue: 6 | Pages: 343-351
Estimates of Time Series Components of Road Traffic Accidents and Effect of Incomplete Observations: Mixed Model Case
K. C. N. Dozie1, C.C Ibebuogu2
1Department of Statistics Imo State University, Owerri, Imo State, Nigeria
2Department of Computer Science Imo State University, Owerri, Imo State, Nigeria
Corresponding Author: K. C. N. Dozie
ABSTRACT
This study examines Buys-Ballot estimates of time series components of road traffic accidents and effect of incomplete observations in descriptive time series analysis. The ultimate objective of this study is therefore, to estimate trend parameters and seasonal indices using Buys-Ballot table with incomplete observations. Specific objectives are 1) to estimate the trend parameters and seasonal indices of the monthly number of road traffic accidents over the period under investigation. 2) to compare the estimates of trend parameters and seasonal indices with and without incomplete observations. 3) to determine the appropriate model. The methods adopted in this study are Regression Imputation (RI) when trend-cycle component is linear, Row Mean Imputation (RMI) and Buys-Ballot table for time series decomposition. The model structure used is mixed.
Keywords: Descriptive Time Series, Missing Data, Trend Parameter, Seasonal Indices, MixedModel, Buys-Ballot Table.
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