Best probability density function for random sampled data (Q845443)
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scientific article; zbMATH DE number 5664182
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Best probability density function for random sampled data |
scientific article; zbMATH DE number 5664182 |
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Best probability density function for random sampled data (English)
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29 January 2010
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Summary: The maximum entropy method is a theoretically sound approach to construct an analytical form for the probability density function (pdf) given a sample of random events. In practice, numerical methods employed to determine the appropriate Lagrange multipliers associated with a set of moments are generally unstable in the presence of noise due to limited sampling. A robust method is presented that always returns the best pdf, where tradeoff in smoothing a highly varying function due to noise can be controlled. An unconventional adaptive simulated annealing technique, called funnel diffusion, determines expansion coefficients for Chebyshev polynomials in the exponential function.
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maximum entropy method
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probability density function
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Lagrange multipliers
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level-function moments
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least squares error
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adaptive simulated annealing
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smoothing noise
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