Abstracts The movement of positive people Coronavirus Disease that was discovered in
2019 (Covid-19), written 2019-nCoV, from one location to another has a great opportunity to …

Monthly data about oil production at several drilling wells is an example of spatio-temporal
data. The aim of this research is to propose nonlinear spatio-temporal model, ie …

ABSTRACT Generalized Space Time Autoregressive (GSTAR) is one of space-time models
that frequently used for forecasting spatio-temporal data. Up to now, the researches about …

The space-time model combines spatial and temporal elements. One example is the
Generalized Space-Time Autoregressive (GSTAR) Model, which improves the Space-Time …

In handling the COVID-19 pandemic, various mitigation policies aiming at slowing the
spread and protecting all individuals, especially the vulnerable ones, were implemented. A …

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 …

Modelling non-negative discrete valued for time series analysis was introduced by previous
researchers, that is Integer-Valued Autoregressive (INAR) model. The model involves both …

The space-time modelling considers the observations dependence based on time and
spatial simultaneously. One of popular models used is the Generalized Space-Time …

Abstract In general, the Generalized Space Time Autoregressive (GSTAR) model of space-
time assumes constant error variance. In this study, a GSTAR model was built with an error …

The release rate of CO2 gas can be influenced by peatlands' physical properties, such as
water level and soil moisture, and rainfall. To anticipate the unstable condition which is …