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Analysis of Generalized Space Time Autoregressive with Exogenous Variable (GSTARX) Model with Outlier Factor
Mukhaiyar U.a, Huda N.M.a, Sari K.N.a, Pasaribu U.S.a
a Statistics Research Group, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 Published under licence by IOP Publishing Ltd.The outlier is an observation data that has different characteristics from others. Frequently, outliers are removed to improve the accuracy of the estimators. But sometimes the presence of an outlier has a specific meaning, which explanation can be lost if the outlier is removed. There are two exceptional cases from types of outliers, Innovative Outlier (IO) and Additive Outlier (AO). The presence of an outlier in the space-time model is no exception. Space-time model, not only influenced by previous observations at the same location and previous observations in a different location, or there are not only time and location dependencies, but also there are some other things that affect, which can be expressed as an exogenous variable. GSTARX is a model that combines not only time and location but also involves exogenous variables. In the GSTARX model, the presence of outliers may also be detected and may have spatial correlation at a time. In this paper, the iterative procedure in detecting outliers in the GSTARX model was introduced. Therefore data containing outliers is not deleted or ignored but still involves the outlier data by adding an outlier factor to the GSTARX model. The power of the procedure in detecting outliers is investigated by simulation experiments. The result is a GSTARX model with outlier factors that maintain the outlier factor.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Additive outliers,Auto-regressive,Exogenous variables,Observation data,Space time,Space-time model,Spatial correlations[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The authors thank to the RISTEK-DIKTI grant, ”Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT)” 2019, The ITB’s program of Research, Community Service and Innovation (P3MI ITB) and ITB Research Program for supporting funds. We also thank to the Health Office of West Kalimantan Province for the data.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1742-6596/1496/1/012004[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]