On the Effect of Seasonal Averages and Standard Deviations on Buys-Ballot Estimates of Time Series Components in the Presence of Missing Values

In this study, we consider the effect of seasonal averages and seasonal standard deviations on Buys-Ballot estimates of time series components in the presence of missing values. The emphasis is to compare seasonal averages with seasonal standard deviations in the presence and absence of missing values using real life example. The methods adopted are Mean Imputation (MI), Regression Imputations (RI) and Buys-Ballot Procedure (BBP) for estimating missing values in time series data. Result of this analysis shows that, the differences between Seasonal averages and seasonal standard deviations with and without missing values have insignificant effect on the Buys-Ballot estimates of time series components.