𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Statistical inference for finite Markov chains based on divergences

✍ Scribed by M.L. Menéndez; D. Morales; L. Pardo; K. Zografos

Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
420 KB
Volume
41
Category
Article
ISSN
0167-7152

No coin nor oath required. For personal study only.

✦ Synopsis

We consider statistical data forming sequences of states of stationary finite irreducible Markov chains, and draw statistical inference about the transition matrix. The inference consists in estimation of parameters of transition probabilities and testing simple and composite hypotheses about them, The inference is based on statistics which are suitable weighted sums of normed ~p-divergences of theoretical row distributions, evaluated at suitable points, and observed empirical row distributions. The asymptotic distribution of minimum ~p-divergence estimators is obtained, as well as critical values of asymptotically a-level tests. (~

📜 SIMILAR VOLUMES

Testing stationary distributions of Mark
Testing stationary distributions of Markov chains based on Rao's divergence
✍ M.C. Pardo 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 310 KB

Statistical inference problems such as the estimation of parameters and testing composite hypothesis about stationary distributions in the set of states of Markov chains are solved. Both, the estimator and the statistic proposed are based on Rao's divergence. The asymptotic properties of the estimat