Pith. sign in

REVIEW 1 cited by

Non singularity of the asymptotic Fisher information matrix in hidden Markov models

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv math/0511631 v1 pith:SMHZRJXC submitted 2005-11-25 math.ST stat.TH

Randal Douc (CMAP) This is my paper · ORCID
classification math.STstat.TH
keywords hiddenfisherinformationmarkovmatrixasymptoticconditionconsider
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

In this paper, we consider a parametric hidden Markov model where the hidden state space is non necessarily finite. We provide a necessary and sufficient condition for the invertibility of the limiting Fisher information matrix.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Statistical Test for Comparing the Linkage and Admixture Model Based on Central Limit Theorems

    math.ST 2025-09 reject novelty 5.0 of 10

    The paper claims to prove consistency and asymptotic normality of MLEs in the Linkage Model and to construct an asymptotic level-alpha likelihood-ratio test for Linkage versus Admixture models, but the proofs contain ...

Pith tools