Name
Abstract | ||
|---|---|---|
The proof of L-2 consistency for the kth nearest neighbour distance estimator of the Shannon entropy for an arbitrary fixed k >= 1 is provided. It is constructed the non-parametric test of goodness-of-fit for a class of introduced generalised multivariate Gaussian distributions based on a maximum entropy principle. The theoretical results are followed by numerical studies on simulated samples. It is shown that increasing of k improves the power of the introduced goodness of fit tests. The asymptotic normality of the test statistics is experimentally proven. (C)& nbsp;2022 Published by Elsevier B.V. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.csda.2022.107502 | COMPUTATIONAL STATISTICS & DATA ANALYSIS |
Keywords | DocType | Volume |
Maximum entropy principle, Generalised Gaussian distribution, Shannon entropy, Nearest neighbour estimator of entropy, Goodness-of-fit test | Journal | 173 |
ISSN | Citations | PageRank |
0167-9473 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mehmet Siddik Cadirci | 1 | 0 | 0.34 |
| Dafydd Evans | 2 | 0 | 0.34 |
| Nikolai Leonenko | 3 | 0 | 0.68 |
| Vitalii Makogin | 4 | 0 | 0.34 |