Checking Serial Independence of Residuals from a Nonlinear Model

Luca Bagnato, Antonio Punzo

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)


In this paper the serial independence tests known as SIS (Serial Independence Simultaneous) and SICS (Serial Independence Chi-Square) are considered. These tests are here contextualized in the model validation phase for nonlinear models in which the underlying assumption of serial independence is tested on the estimated residuals. Simulations are used to explore the performance of the tests, in terms of size and power, once a linear/nonlinear model is fitted on the raw data. Results underline that both the tests are powerful against various types of alternatives.
Original languageEnglish
Title of host publicationChallenges at the Interface of Data Analysis, Computer Science and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization
EditorsWolfgang Gaul, Andreas Geyer-Shulz, Lars Schmidt-Thieme, Jonas Kunze
Number of pages9
Publication statusPublished - 2012


  • Model validation
  • Nonlinear time series


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