Record number :
73380
Title of article :
Non-Gaussian Filter and Smoother Based on the Pearson Distribution System
Author/Authors :
Y.، Nagahara نويسنده ,
Issue Information :
دوماهنامه با شماره پیاپی سال 2003
Pages :
-720
From page :
721
To page :
0
Abstract :
The Pearson distribution system can represent wide class of distributions with various skewness and kurtosis. We develop a practical approach of using all types of its distribution system including the type-IV distribution which was difficult to implement. We propose an easily implemented algorithm which uses less-memory and performs at a higher speed than other typical methods: using analytic approximation of successive conditional probability density functions for prediction and filtering by the Pearson distribution system in the case of both the system and observation noise being one-dimensional. By using the approximated probability density function and the numerical integration, we obtain mean, variance, skewness and kurtosis of the next distribution. We decide the next approximated distribution from the Pearson distribution system. We adopt these steps for the prediction, filtering and smoothing recursively. Our framework makes it possible to construct time series models with various noise distributions. We apply our non-Gaussian filter to the estimation of non-Gaussian stochastic volatility models of the stock returns. We compare our method with the typical method.
Keywords :
Monetary standards and regimes , Government and monetary system
Journal title :
Journal of Time Series Analysis
Serial Year :
2003
Link To Document :
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