2009RePEc: Research Papers in EconomicsRequires access

KERNLDEN2D: MATLAB function to estimate bivariate empirical kernel density function

Shapour Mohammadi

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Abstract

This mfile estimates bivariate empirical kernel density function and mutual information by kernels. Empirical density is evaluated in various pointes that is determined by user as one of inputs. More number of points of evaluation leads to smooth density but it will be computation demanding estimation. It calculates mutual information between x and y as a measure of nonlinear dependency.

About this research paper

What this paper is about

This mfile estimates bivariate empirical kernel density function and mutual information by kernels. Empirical density is evaluated in various pointes that is determined by user as one of inputs. More number of points of evaluation leads to smooth density but it will be computation demanding estimation. It calculates mutual information between x and y as a measure of nonlinear dependency.

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Available abstract

This mfile estimates bivariate empirical kernel density function and mutual information by kernels. Empirical density is evaluated in various pointes that is determined by user as one of inputs. More number of points of evaluation leads to smooth density but it will be computation demanding estimation. It calculates mutual information between x and y as a measure of nonlinear dependency.

Key concepts: Bivariate analysis, Kernel density estimation, Dependency (UML), Kernel (algebra), Mathematics, Multivariate kernel density estimation, Computation, Empirical likelihood

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