Speaker
Mr
Karel Kupka
(TriloByte Statistical Software)
Description
Process stability is usually defined using iid assumption about data. However violating stability requires some concrete model like changepoint, linear trend, outliers, distributional models, positive or negative autocorrelation, etc. These violations are often tested separately and not all of the possible modes of instability can always be taken into account. We suggested a likelihood-based procedure using local regression to assess many possible modes of instability in one step and replace or complement multiple stability tests. The study includes evaluation of equivalent degrees of freedom and AIC/BIC with Monte Carlo simulations and application examples.
| Type of presentation | Talk |
|---|---|
| Classification | Both methodology and application |
| Keywords | Process stability, changepoint, local regression, equivalent degrees of freedom, AIC |
Primary author
Mr
Karel Kupka
(TriloByte Statistical Software)