Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...
The KDE procedure performs either univariate or bivariate kernel density estimation. Statistical density estimation involves approximating a hypothesized probability density function from observed ...
Density estimation is a fundamental component in statistical analysis, aiming to infer the probability distribution of a random variable from a finite sample without imposing restrictive parametric ...
Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 45, No. 2 (1996), pp. 135-150 (16 pages) Motivated by the line transect aerial surveys of Southern Bluefin Tuna in the sea ...
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