Frequency tables are examined in which some cells are not distinguishable. Log-linear models are proposed for these tables which lead to likelihood equations closely related to those associated with log-linear models for conventional frequency tables. Just as in conventional tables, the maximum likelihood equations are shown to be the same under Poisson or multinomial sampling. Applications are made to the problem of estimation of gene frequencies from observed phenotype frequencies.
Publié le : 1974-09-14
Classification:
Log-linear models,
contingency tables,
maximum likelihood estimation,
genetic models,
indirect observation,
62F10,
62P10
@article{1176342813,
author = {Haberman, Shelby J.},
title = {Log-Linear Models for Frequency Tables Derived by Indirect Observation: Maximum Likelihood Equations},
journal = {Ann. Statist.},
volume = {2},
number = {1},
year = {1974},
pages = { 911-924},
language = {en},
url = {http://dml.mathdoc.fr/item/1176342813}
}
Haberman, Shelby J. Log-Linear Models for Frequency Tables Derived by Indirect Observation: Maximum Likelihood Equations. Ann. Statist., Tome 2 (1974) no. 1, pp. 911-924. http://gdmltest.u-ga.fr/item/1176342813/