The American Psychological Association (APA) reports 81% of Gen Z teens (ages 13–17)
have experienced more intense stress during the COVID-19 pandemic. This study uses a …

In predictive modeling with simulation or machine learning, it is critical to assess the quality
of estimated values through output analysis accurately. In recent decades output analysis …

Outlying observations have a large influence on the linear model selection process. In this
article, we present a novel approach to robust model selection in linear regression to …

In prediction problems, it is common to model the data-generating process and then use a
model-based procedure, such as a Bayesian predictive distribution, to quantify uncertainty …

The control chart is very useful and efficient to detect abnormal changes of a process,
however it is difficult to identify out-of-control variables that are responsible for the change …

Lembaga pendidikan tinggi harus bisa menjamin keberhasilan mahasiswa dalam bidang
akademik. Maka lembaga pendidikan tinggi harus dapat membuat model untuk …

Feature Selection (FS) is one of the essential steps in any predictive machine learning (ML)
problem. FS aims to identify the most informative and contributing features (ie, variables) …

In this thesis, we introduce a novel methodology for robust regression analysis when
traditional mean regression falls short due to the presence of heteroscedasticity or outliers …

In Bayesian analysis, uncertainty about quantities of interest—either unknown parameters or
future observations—is quantified using (data-dependent) probabilities. The Bayesian …