2026-10-23T16:12:54Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/00008958 2024-05-27T03:51:38Z 1582963436320 1582963436320:1707206634013

A Seasonal Time Seriws Model of Production Transformers in Hitachi Soe Electric and Machinery Co.,Ltd(2013-2017) (Ma Yu Wah Hlaing, 2018) Yu Wah Hlaing Many economic time series exhibit seasonal behaviour. The estimation of seasonal variation is important problem in time series analysis. Consequently, seasonal variations are needed to determine and seasonal adjustments are needed in forecasting. In this thesis, the production series for transforners for the period of January 2013 to December 2017 are studied. Stochastic models for monthly production series are found by using Box- Jenkins model building approach. Basic statistical characteristics for the production series are first investigated and statistical test for seasonality is applied to each series to confirm the existence of seasonality. Seasonal variation of the production series for transformers from January 2013 to December 2017 are measured by using Ratio to Moving Average Method. Suitable stochastic models for monthly production series are found by following the three stages of model building, namely, identification, estimation and diagnostic checking. Whenever needed, computer programs for the systematic development of the model building procedure are developed. It is found that ARIMA (1,0, 0) x (0,1,0)D, ARIMA (1,0, 0) x (1,1,0)12 ARIMA (1, 1,0) x (1,7,0)pmodels are suitable for our series. Forecasting is very important in future decisions making. The forecast based on the fitted model were also validated in this thesis in order to support future decision making for planning pu{pose. 2018-05-01 https://meral.edu.mm/records/8958