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Posterior Predictive of Bayesian Vector Autoregressive (BVAR) and Adjusting Transformation on the Spatio Temporal Disaggregation Method: Predict Hourly rainfall data at the outsampled Locations

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Title: Posterior Predictive of Bayesian Vector Autoregressive (BVAR) and Adjusting Transformation on the Spatio Temporal Disaggregation Method: Predict Hourly rainfall data at the outsampled Locations

Authors: Suci Astutik, Umu Sa’adah, Supriatna Adhisuwignjo, Rauzan Sumara

Journal: Pakistan Journal of Statistics and Operation Research

HEC Recognition History
Category From To
Y 2020-07-01 2021-06-30

Publisher: Asiatic Region

Country: Pakistan

Year: 2019

Volume: 15

Issue: 2

Language: English

DOI: 10.18187/pjsor.v15i2.2651

Keywords: posterior predictive Bayesian VARadjusting proceduredisaggregationspatio temporal.

Categories
Bayesian Statistics (156) Environmental Science (16313) Time Series Analysis (330) Statistics (8857) Spatial Statistics (12)

Abstract

This research is a development from previous research that has studied the method of spatio temporal disaggregation with State space and adjusting procedures for predicting hourly rainfall based on daily rainfall (Astutik et al, 2013). However, this study is limited to predicting hourly rainfall in some sampled locations in the future. Astutik et al (2017, 2018) have modeled hourly and daily rainfall using posterior predictive bayesian VAR at the Sampean watershed of Bondowoso. This study aims to predict hourly rainfall data based on daily rainfall data in the future at the outsampled locations using posterior predictive bayesian VAR and adjusting procedures in the method of spatio temporal disaggregation.

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