文章基本信息

标题：ESTIMASI PARAMETER MODEL MIXTURE AUTOREGRESSIVE (MAR) MENGGUNAKAN ALGORITMA EKSPEKTASI MAKSIMISASI (EM)
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作者：Mika Asrini ; Winita Sulandari ; Santoso Budi Wiyono 等
期刊名称：MEDIA STATISTIKA
印刷版ISSN：1979-3693
电子版ISSN：2477-0647
出版年度：2013
卷号：6
期号：1
页码：21-26
语种：English
出版社：MEDIA STATISTIKA
摘要：v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} M ixture a utoregressive (MAR) Model is a mixture of Gaussian a utoregressive (AR) components. The mixture model is capable for modelling of nonlinear time series with multimodal conditional distributions. This paper discusses about the parameters estimation using EM algorithm. All possible models are then applied to national maize production data. In this case, the BIC is used for the MAR model selection. Keywords : M ixture A utoregressive, EM A lgorithm, BIC, M aize P roduction Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}