Analysis of Generalized Space Time Autoregressive with Exogenous Variable (GSTARX) Model with Outlier Factor
Space time model, not only influenced by previous observations at the same location and previous observations in 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...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/38805 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Space time model, not only influenced by previous observations at the same location
and previous observations in 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 combine time
and location and involves an exogenous variables. Outlier is an observation data
that has different characteristics from others. Frequently, outliers are removed to
improve accuracy of the estimators. But sometimes the presence of an outlier has
a certain meaning, which explanation can be lost if the outlier is removed. There
are two special cases from types of outliers, Innovative Outlier (IO) and Additive
Outlier (AO). In the GSTARX model, the presence of outliers may also be detected
and may have spatial correlation at a time. In this research, the iterative procedure
in detecting outliers in 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 are investigated by simulation experiments. The result is a GSTARX model
with outlier factors that are free from outlier data |
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