Inference about stationary distributions of Markov chains based on divergences with observed frequencies

Menéndez, María Luisa, et al. "Inference about stationary distributions of Markov chains based on divergences with observed frequencies." Kybernetika 35.3 (1999): [265]-280. <http://eudml.org/doc/33428>.

@article{Menéndez1999,
abstract = {For data generated by stationary Markov chains there are considered estimates of chain parameters minimizing $\phi $–divergences between theoretical and empirical distributions of states. Consistency and asymptotic normality are established and the asymptotic covariance matrices are evaluated. Testing of hypotheses about the stationary distributions based on $\phi $–divergences between the estimated and empirical distributions is considered as well. Asymptotic distributions of $\phi $–divergence test statistics are found, enabling to specify asymptotically $\alpha $-level tests.},
author = {Menéndez, María Luisa, Morales, Domingo, Pardo, Leandro, Vajda, Igor},
journal = {Kybernetika},
keywords = {$\phi $-divergence; empirical distributions; parameter estimation; hypotheses testing; -divergence; empirical distributions; parameter estimation; hypotheses testing},
language = {eng},
number = {3},
pages = {[265]-280},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Inference about stationary distributions of Markov chains based on divergences with observed frequencies},
url = {http://eudml.org/doc/33428},
volume = {35},
year = {1999},
}

TY - JOUR
AU - Menéndez, María Luisa
AU - Morales, Domingo
AU - Pardo, Leandro
AU - Vajda, Igor
TI - Inference about stationary distributions of Markov chains based on divergences with observed frequencies
JO - Kybernetika
PY - 1999
PB - Institute of Information Theory and Automation AS CR
VL - 35
IS - 3
SP - [265]
EP - 280
AB - For data generated by stationary Markov chains there are considered estimates of chain parameters minimizing $\phi $–divergences between theoretical and empirical distributions of states. Consistency and asymptotic normality are established and the asymptotic covariance matrices are evaluated. Testing of hypotheses about the stationary distributions based on $\phi $–divergences between the estimated and empirical distributions is considered as well. Asymptotic distributions of $\phi $–divergence test statistics are found, enabling to specify asymptotically $\alpha $-level tests.
LA - eng
KW - $\phi $-divergence; empirical distributions; parameter estimation; hypotheses testing; -divergence; empirical distributions; parameter estimation; hypotheses testing
UR - http://eudml.org/doc/33428
ER -