{"title":"The Proposed Buys-Ballot Estimates for Multiplicative Model with the Error Variances","authors":"K. Dozie, M. U. Uwaezuoke","doi":"10.9734/jerr/2023/v25i8962","DOIUrl":null,"url":null,"abstract":"This article presents the condition(s) under which the multiplicative model with the error variances best describes the pattern in an observed time series, while comparing it with those of the additive and mixed models. The method of estimation is based on the periodic, seasonal and overall averages and variances of time series data arranged in a Buys-Ballot table. The method assumes that (1) the underlying distribution of the variable, X i j , i = 1, 2, ..., m , j = 1 , 2 , ..., s , under study is normal. (2) the trending curve is linear (3) the decomposition method is either additive or multiplicative or mixed. For multiplicative model, the error variance is not known and needs to be estimated with time series data. For additive and mixed models, the error variances are known and assumed to be equal to 1. Result shows that, under the stated assumptions, the seasonal variances of the Buys-Ballot table, for multiplicative model, a function of column ( j ) through the seasonal component S2j with error variance.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Research and Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/jerr/2023/v25i8962","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents the condition(s) under which the multiplicative model with the error variances best describes the pattern in an observed time series, while comparing it with those of the additive and mixed models. The method of estimation is based on the periodic, seasonal and overall averages and variances of time series data arranged in a Buys-Ballot table. The method assumes that (1) the underlying distribution of the variable, X i j , i = 1, 2, ..., m , j = 1 , 2 , ..., s , under study is normal. (2) the trending curve is linear (3) the decomposition method is either additive or multiplicative or mixed. For multiplicative model, the error variance is not known and needs to be estimated with time series data. For additive and mixed models, the error variances are known and assumed to be equal to 1. Result shows that, under the stated assumptions, the seasonal variances of the Buys-Ballot table, for multiplicative model, a function of column ( j ) through the seasonal component S2j with error variance.
本文提出了带误差方差的乘法模型最能描述观测时间序列模式的条件,并将其与加性模型和混合模型进行了比较。估计方法是根据在投票表中排列的时间序列数据的周期性、季节性和总体平均值和方差。该方法假定(1)变量X i j, i = 1,2,…的底层分布, m, j = 1,2,…, s,在研究中是正常的。(2)趋势曲线为线性;(3)分解方法为加性、乘性或混合性。对于乘法模型,误差方差是未知的,需要用时间序列数据进行估计。对于加性模型和混合模型,误差方差是已知的,并假定为等于1。结果表明,在规定的假设下,对投票表的季节方差,对于乘法模型,列(j)的函数通过季节分量S2j与误差方差。