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Density estimation based on pointwise mutual information

Author

Listed:
  • Akimitsu Inoue

    (Center of Advanced Research and Education, Graduate School of Business, Osaka City University)

Abstract

he purpose of this article is to develop a new bivariate density estimation method based on the decomposition of joint density into pointwise mutual information and marginal densities. The pointwise mutual information and product of marginal densities are estimated by bivariate kernel density estimators with shuffled data. Our method is defined as a product of the marginal densities and pointwise mutual information. Monte-Carlo simulations indicate that this estimation method provides good finite sample performance for weak dependent data.

Suggested Citation

  • Akimitsu Inoue, 2016. "Density estimation based on pointwise mutual information," Economics Bulletin, AccessEcon, vol. 36(2), pages 1138-1148.
    • Handle: RePEc:ebl:ecbull:eb-15-00109
    as

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    References listed on IDEAS

    as
    1. Clark, Allan B. & Lawson, Andrew B., 2004. "An evaluation of non-parametric relative risk estimators for disease maps," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 63-78, August.
    2. Davies, Tilman M. & Hazelton, Martin L. & Marshall, Jonathan. C, 2011. "sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i01).
    3. Dionisio, Andreia & Menezes, Rui & Mendes, Diana A., 2004. "Mutual information: a measure of dependency for nonlinear time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 326-329.
    4. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2003. "Mutual information: a dependence measure for nonlinear time series," Econometrics 0311003, University Library of Munich, Germany.
    5. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    kernel density estimation; pointwise mutual information; density ratio; multivariate density estimation.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    Statistics

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