TITLE:
Comparison of Methods of Estimating Missing Values in Time Series
AUTHORS:
I. S. Iwueze, E. C. Nwogu, V. U. Nlebedim, U. I. Nwosu, U. E. Chinyem
KEYWORDS:
Missing Values, Buys-Ballot Table, Row and Column Averages, Row and Column Variances, Trend Parameters and Seasonal Indices
JOURNAL NAME:
Open Journal of Statistics,
Vol.8 No.2,
April
30,
2018
ABSTRACT: This paper proposes new methods of estimating
missing values in time series data while comparing them with existing methods.
The new methods are based on the row, column and overall averages of time
series data arranged in a Buys-Ballot table with m rows and s columns. The
methods assume that 1) only one value is missing at a time, 2) the trending curve may be linear, quadratic or
exponential and 3) the decomposition method is either Additive or Multiplicative.
The performances of the methods are assessed by comparing accuracy measures
(MAE, MAPE and RMSE) computed from the deviations of estimates of the missing
values from the actual values used in simulation. Results show that, under the
stated assumptions, estimates from the new method based on full decomposition
of a series is the best (in terms of the accuracy measures) when compared with
other two new and the existing methods.