Assessment of Nonlinear Dynamic Models by Kolmogorov-Smirnov Statistics

作者：Djuric Petar M^*; Miguez Joaquin

来源：IEEE Transactions on Signal Processing, 2010, 58(10): 5069-5079.

DOI：10.1109/TSP.2010.2053707

• Cumulative distributions
• Kolomogorov-Smirnov statistics
• model assessment
• particle filtering
• predictive distributions

Model assessment is a fundamental problem in science and engineering and it addresses the question of the validity of a model in the light of empirical evidence. In this paper, we propose a method for the assessment of dynamic nonlinear models based on empirical and predictive cumulative distributions of data and the Kolmogorov-Smirnov statistics. The technique is based on the generation of discrete random variables that come from a known discrete distribution if the entertained model is correct. We provide simulation examples that demonstrate the performance of the proposed method.

• 出版日期2010-10