Interval estimation of the mass fractal dimension for isotropic sampling percolation clusters
P.V. Moskalev, K.V. Grebennikov, V.V. Shitov
TL;DR
This paper investigates how to accurately estimate the mass fractal dimension of isotropic percolation clusters by analyzing confidence interval dependencies in the sampling process.
Contribution
It introduces a method to analyze the dependencies affecting confidence intervals in mass fractal dimension estimation for isotropic percolation clusters.
Findings
Identified key factors influencing confidence interval centers and radii.
Provided a framework for more reliable fractal dimension estimation.
Enhanced understanding of sampling effects on percolation cluster analysis.
Abstract
This report focuses on the dependencies for the center and radius of the confidence interval that arise when estimating the mass fractal dimensions of isotropic sampling clusters in the site percolation model.
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Taxonomy
TopicsStochastic processes and statistical mechanics · Bayesian Methods and Mixture Models · Theoretical and Computational Physics