Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 148 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 34 tok/s Pro
GPT-5 High 40 tok/s Pro
GPT-4o 101 tok/s Pro
Kimi K2 183 tok/s Pro
GPT OSS 120B 443 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Reparametrization of the least favorable submodel in semi-parametric multisample models (1205.1920v1)

Published 9 May 2012 in math.ST and stat.TH

Abstract: The method of estimation in Scott and Wild (Biometrika 84 (1997) 57--71 and J. Statist. Plann. Inference 96 (2001) 3--27) uses a reparametrization of the profile likelihood that often reduces the computation times dramatically. Showing the efficiency of estimators for this method has been a challenging problem. In this paper, we try to solve the problem by investigating conditions under which the efficient score function and the efficient information matrix can be expressed in terms of the parameters in the reparametrized model.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (2)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.