English
Related papers

Related papers: On optimal designs for non-regular models

200 papers

In statistical modeling area, the Akaike information criterion AIC, is a widely known and extensively used tool for model choice. The {\phi}-divergence test statistic is a recently developed tool for statistical model selection. The…

Methodology · Statistics 2011-10-28 Papa Ngom , Bertrand Ntep

Fisher matrices play an important role in experimental design and in data analysis. Their primary role is to make predictions for the inference of model parameters - both their errors and covariances. In this short review, I outline a…

Cosmology and Nongalactic Astrophysics · Physics 2016-08-24 Alan Heavens

This paper considers the problem of determining an optimal control action based on observed data. We formulate the problem assuming that the system can be modelled by a nonlinear state-space model, but where the model parameters, state and…

Optimization and Control · Mathematics 2021-07-02 Johannes N. Hendriks , James R. Z. Holdsworth , Adrian G. Wills , Thomas B. Schon , Brett Ninness

This paper extends the idea of a generalized estimator for a scalar parameter (Vos, 2022) to multi-dimensional parameters both with and without nuisance parameters. The title reflects the fact that generalized estimators provide more than…

Statistics Theory · Mathematics 2024-08-26 Paul Vos , Qiang Wu

Optimal experimental design is a classic topic in statistics, with many well-studied problems, applications, and solutions. The design problem we study is the placement of sensors to monitor spatiotemporal processes, explicitly accounting…

Methodology · Statistics 2026-01-05 Daniel Waxman , Fernando Llorente , Katia Lamer , Petar M. Djurić

We consider approximate Bayesian model choice for model selection problems that involve models whose Fisher-information matrices may fail to be invertible along other competing submodels. Such singular models do not obey the regularity…

Methodology · Statistics 2016-03-24 Mathias Drton , Martyn Plummer

This paper is a strongly geometrical approach to the Fisher distance, which is a measure of dissimilarity between two probability distribution functions. The Fisher distance, as well as other divergence measures, are also used in many…

Methodology · Statistics 2014-01-13 Sueli I. R. Costa , Sandra A. Santos , João E. Strapasson

The Schrodinger equation can be derived using the minimum Fisher information principle. I discuss why such an approach should work, and also show that the Kahler and Hilbert space structures of quantum mechanics result from combining the…

Quantum Physics · Physics 2007-05-23 Marcel Reginatto

We propose a method to remedy finite sample coverage problems and improve upon the efficiency of commonly employed procedures for the construction of nonparametric confidence intervals in regression kink designs. The proposed interval is…

Econometrics · Economics 2021-11-23 Majed Dodin

Pairwise comparison models have been widely used for utility evaluation and rank aggregation across various fields. The increasing scale of modern problems underscores the need to understand statistical inference in these models when the…

Statistics Theory · Mathematics 2025-12-16 Ruijian Han , Wenlu Tang , Yiming Xu

We show that both the classical as well as the quantum definitions of the Fisher information faithfully identify resourceful quantum states in general quantum resource theories, in the sense that they can always distinguish between states…

Quantum Physics · Physics 2021-11-25 Kok Chuan Tan , Varun Narasimhachar , Bartosz Regula

Basic general properties are considered for the Fisher-type information involving higher order derivatives. They are used to explore various properties of probability densities and to derive Stam-type inequalities.

Information Theory · Computer Science 2024-12-16 Sergey G. Bobkov

Bayesian optimal experimental design (OED) provides a principled framework for selecting observations or experiments. We introduce new Bayesian design criteria based on the expected Wasserstein-$p$ distance between the prior and posterior…

Methodology · Statistics 2026-05-28 Tapio Helin , Youssef Marzouk , Jose Rodrigo Rojo-Garcia

Tie-breaker designs trade off a statistical design objective with short-term gain from preferentially assigning a binary treatment to those with high values of a running variable $x$. The design objective is any continuous function of the…

Methodology · Statistics 2022-10-20 Harrison H. Li , Art B. Owen

In recent proposals for achieving optical super-resolution, variants of the Quantum Fisher Information (QFI) quantify the attainable precision. We find that claims about a strong enhancement of the resolution resulting from coherence…

Quantum Physics · Physics 2019-11-14 Zdeněk Hradil , Jaroslav Řeháček , Luis Sánchez-Soto , Berthold-Georg Englert

We study the problem of estimating a continuous ability parameter from sequential binary responses by actively asking questions with varying difficulties, a setting that arises naturally in adaptive testing and online preference learning.…

Machine Learning · Statistics 2025-10-10 Sanghwa Kim , Dohyun Ahn , Seungki Min

In the context of the usual calibration model, we consider the case in which the independent variable is unobservable, but a pre-fixed value on its surrogate is available. Thus, considering controlled variables and assuming that the…

Applications · Statistics 2008-02-06 Betsabé G. Blas Achic , Mônica C. Sandoval , Olga Satomi Yoshida

In quantum resource theory (QRT), asymmetry recognized as a valid resource for the advantage of various quantum information processing. In this paper, we establish the resource theory of asymmetry using quantum Fisher information (QFI). By…

Quantum Physics · Physics 2021-10-07 R. Muthuganesan , V. K. Chandrasekar

How to design a Markov Decision Process (MDP) based radar controller that makes small sacrifices in performance to mask its sensing plan from an adversary? The radar controller purposefully minimizes the Fisher information of its emissions…

Systems and Control · Electrical Eng. & Systems 2024-03-26 Shashwat Jain , Vikram Krishnamurthy , Muralidhar Rangaswamy , Bosung Kang , Sandeep Gogineni

A decision maker typically (i) incorporates training data to learn about the relative effectiveness of treatments, and (ii) chooses an implementation mechanism that implies an ``optimal'' predicted outcome distribution according to some…

Econometrics · Economics 2025-05-29 Anders Bredahl Kock , David Preinerstorfer
‹ Prev 1 8 9 10 Next ›