| Title |
A consistent estimator of structural distribution / |
| Authors |
Radavičius, Marijus |
| DOI |
10.17713/ajs.v49i4.1135 |
| Full Text |
|
| Is Part of |
Austrian journal of statistics: Special Issue CDAM 2019.. Wien : The Austrian Statistical Society. 2020, vol. 49, iss. 4, spec. iss. SI, p. 99-105.. ISSN 1026-597X |
| Keywords [eng] |
structural distribution ; Poisson mixture ; sparsity rate ; nonparametric estimator ; consistency ; weak convergence |
| Abstract [eng] |
We consider sparse count data models with the sparsity rate r = N/n = O(1) where N = N (n) is the number of observations and n is the number of cells. In this case the plug-in estimator of the structural distribution of expected frequencies is inconsistent. If r = O(n^{-q }) for some q > 0, the nonparametric maximum likelihood estimator, in general, is also inconsistent. Assuming that some auxiliary information on the expected frequencies is available, we construct a consistent estimator of the structural distribution. |
| Published |
Wien : The Austrian Statistical Society |
| Type |
Journal article |
| Language |
English |
| Publication date |
2020 |
| CC license |
|
