Ryan Glenn Martin

Works (72)

Updated: October 25th, 2024 05:01

2024 journal article

Empirical Bayes inference in sparse high-dimensional generalized linear models

ELECTRONIC JOURNAL OF STATISTICS, 18(2), 3212–3246.

By: Y. Tang* & R. Martin n

author keywords: Data-dependent prior; logistic regression; model selection; Poisson log-linear model; posterior asymptotics
Source: Web Of Science
Added: October 8, 2024

2024 article

Large-Sample Theory for Inferential Models: A Possibilistic Bernstein-von Mises Theorem

BELIEF FUNCTIONS: THEORY AND APPLICATIONS, BELIEF 2024, Vol. 14909, pp. 111–120.

By: R. Martin* & J. Williams*

author keywords: Asymptotics; Bayesian; belief; fiducial; relative likelihood
Source: Web Of Science
Added: October 21, 2024

2024 journal article

Turning the information-sharing dial: Efficient inference from different data sources

ELECTRONIC JOURNAL OF STATISTICS, 18(2), 2974–3020.

By: E. Hector n & R. Martin n

author keywords: Data enrichment; generalized linear models; Kullback-Leibler divergence; transfer learning; ridge regression
Sources: Web Of Science, NC State University Libraries
Added: October 8, 2024

2024 article

Variational Approximations of Possibilistic Inferential Models

BELIEF FUNCTIONS: THEORY AND APPLICATIONS, BELIEF 2024, Vol. 14909, pp. 121–130.

By: L. Cellal & R. Martini

author keywords: Confidence regions; credal set; Monte Carlo; statistical inference; stochastic approximation
Source: Web Of Science
Added: October 21, 2024

2024 article

Which Statistical Hypotheses are Afflicted with False Confidence?

BELIEF FUNCTIONS: THEORY AND APPLICATIONS, BELIEF 2024, Vol. 14909, pp. 140–149.

By: R. Martin*

author keywords: Bayesian; consonant beliefs; convexity; inferential model; fiducial inference; possibility theory; validity
Source: Web Of Science
Added: October 21, 2024

2023 journal article

A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions

STATISTICS AND COMPUTING, 33(4).

By: V. Dixit n & R. Martin n

author keywords: Importance sampling; Marked point process; Mixture model; Monte Carlo; Predictive recursion
TL;DR: A new strategy is proposed, which is referred to as PRticle filter, wherein the basic PR algorithm is augmented with a filtering mechanism that adaptively reweights an initial set of particles along the updating sequence which are used to obtain Monte Carlo approximations of the normalizing constants. (via Semantic Scholar)
Source: Web Of Science
Added: May 30, 2023

2023 journal article

Gibbs posterior concentration rates under sub-exponential type losses

BERNOULLI, 29(2), 1080–1108.

By: N. Syring* & R. Martin n

author keywords: Classification; generalized Bayes; high-dimensional problem; M-estimation; model misspecification
TL;DR: This work provides simple sufficient conditions for establishing Gibbs posterior concentration rates when the loss function is of a sub-exponential type and applies these techniques in an important problem in medical statistics, namely, estimation of a personalized minimum clinically important difference. (via Semantic Scholar)
Source: Web Of Science
Added: April 4, 2023

2023 journal article

Possibility-theoretic statistical inference offers performance and probativeness assurances

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 163.

By: L. Cella* & R. Martin n

author keywords: Bayesian; Frequentist; Imprecise probability; Inferential model; Severity; Validity
TL;DR: It is demonstrated that valid inferential models (IMs) achieve both performance and probativeness properties and a powerful new result is offered that ensures the IM's probing is reliable. (via Semantic Scholar)
Source: Web Of Science
Added: January 2, 2024

2023 journal article

Revisiting consistency of a recursive estimator of mixing distributions

ELECTRONIC JOURNAL OF STATISTICS, 17(1), 1007–1042.

By: V. Dixit n & R. Martin n

author keywords: Deconvolution; mixture model; monotone density estimation; predictive recursion; robustness
Source: Web Of Science
Added: November 20, 2023

2023 journal article

Ryan Martin's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 86(1).

By: R. Martin n

Source: Web Of Science
Added: March 4, 2024

2022 journal article

A Comparison of Learning Rate Selection Methods in Generalized Bayesian Inference

BAYESIAN ANALYSIS, 18(1), 105–132.

By: P. Wu n & R. Martin n

author keywords: coverage probability; generalized posterior calibration algorithm; model misspecification; SafeBayes algorithm
TL;DR: This paper provides a direct head-to-head comparison of these learning rate selection methods in various misspecified model scenarios, in terms of several relevant metrics, in particular, coverage probability of the generalized Bayes credible regions. (via Semantic Scholar)
Source: Web Of Science
Added: February 27, 2023

2022 article

A Practical Strategy for Valid Partial Prior-Dependent Possibilistic Inference

BELIEF FUNCTIONS: THEORY AND APPLICATIONS (BELIEF 2022), Vol. 13506, pp. 197–206.

By: D. Hose*, M. Hanss* & R. Martin n

author keywords: Bayesian; Choquet integral; Credal set; Fisher; Frequentist; Inferential model; Likelihood; Possibility theory
Source: Web Of Science
Added: November 14, 2022

2022 article

Direct Gibbs posterior inference on risk minimizers: Construction, concentration, and calibration

ADVANCEMENTS IN BAYESIAN METHODS AND IMPLEMENTATION, Vol. 47, pp. 1–41.

By: R. Martin n & N. Syring*

author keywords: Asymptotics; Empirical risk minimization; Bayesian inference; Learning rate; M-estimation; Model misspecification; Statistical learning
Source: Web Of Science
Added: January 2, 2024

2022 journal article

Direct and approximately valid probabilistic inference on a class of statistical functionals

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 151, 205–224.

By: L. Cella* & R. Martin n

author keywords: Bootstrap; Empirical risk minimizer; M-estimator; Nonparametric; Plausibility function; Z-estimator
TL;DR: A generalized inferential model (IM) framework for direct probabilistic uncertainty quantification on the quantity of interest is developed and it is proved that this new approach provides approximately valid inference in the sense that the plausibility values assigned to hypotheses about the unknowns are asymptotically well-calibrated in a frequentist sense. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Web Of Science
Added: November 28, 2022

2022 article

Estimating a Mixing Distribution on the Sphere Using Predictive Recursion

Dixit, V., & Martin, R. (2022, February 10). SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS.

By: V. Dixit n & R. Martin n

author keywords: Directional data; EM algorithm; Marginal likelihood; Mixture model; Von Mises-Fisher distribution
TL;DR: Using the predictive recursion (PR) algorithm to solve for a mixture on a sphere, PR’s asymptotic consistency in spherical mixture models is established, and simulation results showcase its benefits compared to existing likelihood-based methods. (via Semantic Scholar)
Source: Web Of Science
Added: February 28, 2022

2022 article

Valid Inferential Models Offer Performance and Probativeness Assurances

BELIEF FUNCTIONS: THEORY AND APPLICATIONS (BELIEF 2022), Vol. 13506, pp. 219–228.

By: L. Cella n & R. Martin n

author keywords: Bayesian; Frequentist; p-value; Possibility measure; Severity
Source: Web Of Science
Added: November 14, 2022

2022 article

Valid Model-Free Spatial Prediction

Mao, H., Martin, R., & Reich, B. J. J. (2022, December 17). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 12.

By: H. Mao*, R. Martin n & B. Reich n

author keywords: Conformal prediction; Gaussian process; Kriging; Nonstationary; Plausibility
Sources: Web Of Science, NC State University Libraries
Added: January 23, 2023

2022 journal article

Valid inferential models for prediction in supervised learning problems

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 150, 1–18.

By: L. Cella n & R. Martin n

author keywords: Classification; Conformal prediction; Plausibility contour; Random sets; Regression
TL;DR: It is shown that valid Probabilistic predictors avoid sure loss and lead to prediction procedures with desirable frequentist error rate control properties and a general inferential model construction that yields a provably valid probabilistic predictor is provided. (via Semantic Scholar)
Source: Web Of Science
Added: October 17, 2022

2021 article

Approximately Valid and Model-Free Possibilistic Inference

BELIEF FUNCTIONS: THEORY AND APPLICATIONS (BELIEF 2021), Vol. 12915, pp. 127–136.

By: L. Cella n & R. Martin n

author keywords: Belief; Bootstrap; Inferential model; M-estimation; Plausibility; Quantile regression
Source: Web Of Science
Added: December 6, 2021

2021 journal article

Bayesian estimation of sparse precision matrices in the presence of Gaussian measurement error

ELECTRONIC JOURNAL OF STATISTICS, 15(2), 4545–4579.

By: W. Shi n, S. Ghosal n & R. Martin n

author keywords: High-dimensional inference; Gaussian graphical model; measurement error; posterior contraction rate; sparsity
TL;DR: This paper incorporates measurement error in the context of estimating a sparse, high-dimensional precision matrix for a Gaussian graphical model with data corrupted by Gaussian measurement error with unknown variance and establishes a general result which gives sufficient conditions under which the posterior contraction rates that hold in the no-measurement-error case carry over to the measurement- error case. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: February 28, 2022

2021 article

Comment: Settle the Unsettling: An Inferential Models Perspective

Liu, C., & Martin, R. (2021, May). STATISTICAL SCIENCE, Vol. 36, pp. 196–200.

By: C. Liu* & R. Martin n

author keywords: Belief function; efficiency; lower and upper probability; inferential models; validity
TL;DR: It is demonstrated that the inferential model (IM) framework, unlike the updating rules that Gong and Meng show to be unreliable, provides valid and efficient inferences/prediction while not being susceptible to sure loss. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 9, 2021

2021 journal article

Generalized inferential models for censored data

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 137, 51–66.

By: J. Cahoon* & R. Martin n

author keywords: Kaplan-Meier estimator; Plausibility; Random set; Relative likelihood; Survival analysis
TL;DR: This paper provides an alternative generalized inferential model approach whose output is a data-dependent plausibility function, driven by an association between the distribution of the relative likelihood function at the interest parameter and an unobserved auxiliary variable. (via Semantic Scholar)
Source: Web Of Science
Added: February 28, 2022

2021 journal article

Gibbs posterior inference on multivariate quantiles

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 218, 106–121.

By: I. Bhattacharya* & R. Martin n

author keywords: Bernstein-von Mises phenomenon; Concentration rate; Credible sets; Learning rate; Multivariate median
TL;DR: A direct and model-free Gibbs posterior distribution for multivariate quantiles is constructed, which means that inferences drawn from the Gibbs posterior are not subject to model misspecification bias, and being direct means that no priors for or marginalization over nuisance parameters are required. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Web Of Science
Added: November 23, 2021

2021 article

Imprecise credibility theory

Hong, L., & Martin, R. (2021, April 15). ANNALS OF ACTUARIAL SCIENCE.

By: L. Hong* & R. Martin n

author keywords: Imprecise probability; Credibility estimator; Model misspecification; Prior uncertainty; Robustness
Source: Web Of Science
Added: December 13, 2021

2021 personal communication

Response to the comment Confidence in confidence distributions!

Martin, R., Balch, M. S., & Ferson, S. (2021, June 30).

By: R. Martin n, M. Balch* & S. Ferson*

author keywords: false confidence; non-additive beliefs; inferential model; satellite conjunction analysis
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: July 19, 2021

2021 article

Ryan Martin's contribution to the Discussion of 'Testing by betting: A strategy for statistical and scientific communication' by Glenn Shafer

Martin, R. (2021, April). JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol. 184, pp. 456–457.

By: R. Martin n

UN Sustainable Development Goal Categories
Source: Web Of Science
Added: June 10, 2021

2021 article

Towards a Theory of Valid Inferential Models with Partial Prior Information

BELIEF FUNCTIONS: THEORY AND APPLICATIONS (BELIEF 2021), Vol. 12915, pp. 137–146.

By: R. Martin n

author keywords: Belief function; Coherence; Consonance; Generalized bayes; Possibility measure; Statistical inference
Source: Web Of Science
Added: December 6, 2021

2021 journal article

Validity, consonant plausibility measures, and conformal prediction

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 141, 110–130.

By: L. Cella n & R. Martin n

author keywords: Belief function; Coherence; Inferential model; Possibility measure; Random set
TL;DR: This work establishes connections between Type-2 validity and coherence properties, and shows that imprecise probability considerations are required in order to achieve it, and goes on to show that both types of prediction validity can be achieved by interpreting the conformal prediction output as the contour function of a consonant plausibility measure. (via Semantic Scholar)
Source: Web Of Science
Added: August 8, 2022

2020 journal article

BAYESIAN INFERENCE IN HIGH-DIMENSIONAL LINEAR MODELS USING AN EMPIRICAL CORRELATION-ADAPTIVE PRIOR

STATISTICA SINICA, 31(4), 2051–2072.

By: C. Liu n, Y. Yang n, H. Bondell* & R. Martin n

author keywords: Collinearity; empirical Bayes; posterior convergence rate; stochastic search; variable selection
TL;DR: An empirical correlation-adaptive prior that makes use of information in the observed predictor variable matrix to adaptively address high collinearity, determining if parameters associated with correlated predictors should be shrunk together or kept apart is proposed. (via Semantic Scholar)
Source: Web Of Science
Added: March 7, 2022

2020 journal article

Model misspecification, Bayesian versus credibility estimation, and Gibbs posteriors

SCANDINAVIAN ACTUARIAL JOURNAL, 2020(7), 634–649.

By: L. Hong* & R. Martin n

author keywords: Asymptotics; Bernstein-von Mises phenomenon; exponential family; robustness; uncertainty quantification
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: January 27, 2020

2020 journal article

Model-free posterior inference on the area under the receiver operating characteristic curve

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 209, 174–186.

By: Z. Wang n & R. Martin n

author keywords: Credible interval; Gibbs posterior; Generalized bayesian inference; Model misspecification; Robustness
TL;DR: A direct and model-free Gibbs posterior distribution for inference on the AUC is developed and the asymptotic Gibbs posterior concentration rate is presented, and a strategy for tuning the learning rate so that the corresponding credible intervals achieve the nominal frequentist coverage probability. (via Semantic Scholar)
Source: Web Of Science
Added: May 26, 2020

2020 journal article

ROBUST AND RATE-OPTIMAL GIBBS POSTERIOR INFERENCE ON THE BOUNDARY OF A NOISY IMAGE

ANNALS OF STATISTICS, 48(3), 1498–1513.

By: N. Syring* & R. Martin n

author keywords: Adaptation; boundary detection; likelihood-free inference; model misspecification; posterior concentration rate
TL;DR: A robust Gibbs approach is developed that constructs a posterior distribution for the image boundary directly, without modeling the pixel intensities, and it is proved that, for a suitable prior on theimage boundary, the Gibbs posterior concentrates asymptotically at the minimax optimal rate, adaptive to the boundary smoothness. (via Semantic Scholar)
Source: Web Of Science
Added: August 10, 2020

2020 journal article

Valid Model-Free Prediction of Future Insurance Claims

NORTH AMERICAN ACTUARIAL JOURNAL, 25(4), 473–483.

By: L. Hong* & R. Martin n

UN Sustainable Development Goal Categories
Source: Web Of Science
Added: February 28, 2022

2019 journal article

A Survey of Nonparametric Mixing Density Estimation via the Predictive Recursion Algorithm

SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS, 83(1), 97–121.

By: R. Martin n

author keywords: Empirical Bayes; high-dimensional inference; Jayanta K; Ghosh; mixture model; recursive estimation
TL;DR: This paper surveys the literature on a fast, recursive estimator based on the predictive recursion algorithm, summarizes the available asymptotic convergence theory, describes an important semiparametric extension, and highlights two interesting applications. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: November 11, 2019

2019 journal article

Bayesian Test of Normality Versus a Dirichlet Process Mixture Alternative

SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS, 83(1), 66–96.

By: S. Tokdar* & R. Martin n

author keywords: Bayes factor; embedding; goodness-of-fit; importance sampling; noninformative prior; predictive matching
TL;DR: Simulations indicate the proposed Bayesian test of normality for univariate or multivariate data against alternative nonparametric models characterized by Dirichlet process mixture distributions can detect non-normality without favoring the non parametric alternative when normality holds. (via Semantic Scholar)
Source: Web Of Science
Added: August 24, 2020

2019 journal article

Data-driven priors and their posterior concentration rates

ELECTRONIC JOURNAL OF STATISTICS, 13(2), 3049–3081.

By: R. Martin n & S. Walker*

author keywords: Adaptation; data-dependent prior; density estimation; empirical Bayes; nonparametric regression
TL;DR: This paper develops a general strategy for constructing a data-driven or empirical prior and sufficient conditions for the corresponding posterior distribution to achieve a certain concentration rate and presents results on both adaptive and non-adaptive rates based on empirical priors. (via Semantic Scholar)
Source: Web Of Science
Added: January 27, 2020

2019 journal article

Discussion of 'Nonparametric generalized fiducial inference for survival functions under censoring'

BIOMETRIKA, 106(3), 519–522.

By: R. Martin n

UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Source: Web Of Science
Added: November 18, 2019

2019 journal article

Empirical Priors and Coverage of Posterior Credible Sets in a Sparse Normal Mean Model

SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY, 82(2), 477–498.

By: R. Martin n & B. Ning*

author keywords: Bayesian inference; Bernstein-von Mises theorem; Concentration rate; High-dimensional model; Uncertainty quantification
Source: Web Of Science
Added: December 30, 2019

2019 article

False confidence, non-additive beliefs, and valid statistical inference

Martin, R. (2019, October). INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, Vol. 113, pp. 39–73.

By: R. Martin n

author keywords: Bayes; Fiducial; Inferential model; p-Value; Plausibility function; Random set
Source: Web Of Science
Added: October 7, 2019

2019 journal article

Gibbs posterior inference on value-at-risk

SCANDINAVIAN ACTUARIAL JOURNAL, (7), 548–557.

By: N. Syring*, L. Hong* & R. Martin n

author keywords: Direct posterior; discrepancy function; M-estimation; model misspecification; risk capital; robust estimation
TL;DR: This paper links data and VaR directly via what is called a discrepancy function, and this leads naturally to a Gibbs posterior distribution for VaR that does not suffer from the aforementioned biases and inefficiencies. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 12, 2019

2019 journal article

ON OPTIMAL DESIGNS FOR NONREGULAR MODELS

ANNALS OF STATISTICS, 47(6), 3335–3359.

By: Y. Lin n, R. Martin n & M. Yang n

author keywords: E-optimality; experimental design; Fisher information; Hellinger distance; information inequality
TL;DR: A Hellinger information inequality is derived, showing that Hellinginger information defines a lower bound on the local minimax risk of estimators, motivating the use of this new Helleder information for non-regular optimal design problems, with numerical results empirically demonstrating the improved efficiency of these designs compared to alternatives. (via Semantic Scholar)
UN Sustainable Development Goal Categories
2. Zero Hunger (Web of Science)
Source: Web Of Science
Added: November 18, 2019

2019 journal article

Satellite conjunction analysis and the false confidence theorem

By: M. Balch, R. Martin n & S. Ferson*

author keywords: belief functions; filter estimates; space situational awareness; statistical theory and methods
TL;DR: The Martin–Liu validity criterion is introduced as a benchmark by which to identify statistical methods that are free from false confidence, and it is shown that uncertainty ellipsoids satisfy the validity criterion. (via Semantic Scholar)
Source: Web Of Science
Added: August 26, 2019

2019 review

Ten Hot Topics around Scholarly Publishing

[Review of ]. PUBLICATIONS, 7(2).

By: J. Tennant*, H. Crane*, T. Crick*, J. Davila*, A. Enkhbayar*, J. Havemann, B. Kramer*, R. Martin n ...

author keywords: peer review; copyright; open access; open science; scholarly communication; web of science; Scopus; impact factor; research evaluation
TL;DR: A baseline evidence framework is provided for ten of the most contested topics, including issues around preprints and scooping, the practice of copyright transfer, the function of peer review, predatory publishers, and the legitimacy of ‘global’ databases. (via Semantic Scholar)
Source: Web Of Science
Added: July 29, 2019

2018 journal article

Convergence of an iterative algorithm to the nonparametric MLE of a mixing distribution

STATISTICS & PROBABILITY LETTERS, 140, 142–146.

By: M. Chae*, R. Martin n & S. Walker*

author keywords: Bayesian update; Deconvolution; Mixture model; Predictive recursion; Smoothing
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2018 journal article

Empirical Priors and Posterior Concentration Rates for a Monotone Density

Sankhya A, 81(2), 493–509.

By: R. Martin n

author keywords: Density estimation; Empirical Bayes; Grenander estimator; Mixture model; Shape constraint
Sources: Web Of Science, Crossref
Added: February 27, 2020

2018 journal article

Miscellanea Calibrating general posterior credible regions

BIOMETRIKA, 106(2), 479–486.

By: N. Syring* & R. Martin n

author keywords: Bootstrap; Coverage probability; Gibbs posterior distribution; Model misspecification; Stochastic approximation
TL;DR: A scalar tuning parameter is introduced that controls the posterior distribution spread, and a Monte Carlo algorithm is developed that sets this parameter so that the corresponding credible region achieves the nominal frequentist coverage probability. (via Semantic Scholar)
Source: Web Of Science
Added: November 11, 2019

2018 journal article

On an algorithm for solving Fredholm integrals of the first kind

STATISTICS AND COMPUTING, 29(4), 645–654.

By: M. Chae*, R. Martin n & S. Walker*

author keywords: Brownian motion first passage time; Convergence; Expectation-maximization; Iterative algorithm; Mixture model
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: June 17, 2019

2018 journal article

Real-time Bayesian non-parametric prediction of solvency risk

ANNALS OF ACTUARIAL SCIENCE, 13(1), 67–79.

By: L. Hong* & R. Martin n

author keywords: Density estimation; Mixture model; Non-parametric Bayes; Risk management; Value-at-risk
TL;DR: This approach facilitates recursive Bayesian prediction without computing a posterior, allowing insurers to perform real-time updating of risk measures to assess solvency risk, and providing them with a tool for carrying out dynamic risk management strategies in today’s “big data” era. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: February 11, 2019

2017 journal article

'Purposely misspecified' posterior inference on the volatility of a jump diffusion process

STATISTICS & PROBABILITY LETTERS, 134, 106–113.

By: R. Martin n, C. Ouyang* & F. Domagni*

author keywords: Bernstein-von Mises theorem; Cramer-Rao lower bound; Credible interval; Gibbs posterior; Uncertainty quantification
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2017 review

A review of Bayesian asymptotics in general insurance applications

[Review of ]. EUROPEAN ACTUARIAL JOURNAL, 7(1), 231–255.

By: L. Hong* & R. Martin n

author keywords: General insurance; Nonparametric Bayes; Posterior consistency; Posterior robustness; Property and casualty insurance
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2017 journal article

Dirichlet process mixture models for insurance loss data

SCANDINAVIAN ACTUARIAL JOURNAL, (6), 545–554.

By: L. Hong* & R. Martin n

author keywords: Danish fire losses data; general insurance; model misspecification; nonparametric Bayes; Norwegian fire losses data; property and casualty insurance; US allocated loss adjustment expenses data
TL;DR: This paper reanalyzes several of the standard insurance data-sets to support the claim that model misspecification biases can be avoided by taking a nonparametric approach, with little to no cost, compared to existing parametric approaches. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2017 journal article

Gibbs posterior inference on the minimum clinically important difference

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 187, 67–77.

By: N. Syring n & R. Martin n

author keywords: Clinical significance; Loss function; M-estimation; Model-free inference; Posterior convergence rate
TL;DR: A likelihood-free posterior distribution is constructed for the minimum clinically important difference (MCID) and it is shown, numerically, that an appropriately scaled version the posterior yields interval estimates for the MCID which are both valid and efficient even for relatively small sample sizes. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2017 journal article

On Recursive Bayesian Predictive Distributions

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 113(523), 1085–1093.

By: P. Hahn*, R. Martin n & S. Walker*

author keywords: Copula; Density estimation; Nonparametric Bayes; Prediction; Recursive estimation
TL;DR: This article shows that online Bayesian prediction is possible by characterizing the Bayesian predictive update in terms of a bivariate copula, making it unnecessary to pass through the posterior to update the predictive. (via Semantic Scholar)
Source: Web Of Science
Added: October 29, 2018

2017 journal article

On overfitting and post-selection uncertainty assessments

BIOMETRIKA, 105(1), 221–224.

By: L. Hong*, T. Kuffner* & R. Martin n

author keywords: Akaike information criterion; Bayesian information criterion; Model selection; Regression
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2017 journal article

Uncertainty quantification for the horseshoe (with discussion) comment

Bayesian Analysis, 12(4), 1254–1258.

By: R. Martin

Source: NC State University Libraries
Added: August 6, 2018

2016 journal article

A Conversation with Samad Hedayat

STATISTICAL SCIENCE, 31(4), 637–647.

By: R. Martin n, J. Stufken n & M. Yang n

author keywords: Design of experiments; survey sampling; biostatistics; statistical research; statistical consulting; advising students
TL;DR: This conversation touches on Professor Hedayat’s career, and the past, present and future of statistics, and offers an abundance of advice for students and junior faculty. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2016 journal article

A Statistical Inference Course Based on p-Values

AMERICAN STATISTICIAN, 71(2), 128–136.

By: R. Martin n

author keywords: Confidence interval; Large-sample theory; Monte Carlo; Teaching statistics; Valid inference
TL;DR: An alternative approach to teaching this course is presented, built around p-values, emphasizing provably valid inference for all sample sizes. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2016 journal article

Efficient simulation from a gamma distribution with small shape parameter

COMPUTATIONAL STATISTICS, 32(4), 1767–1775.

By: C. Liu*, R. Martin n & N. Syring n

author keywords: Acceptance rate; Acceptance-rejection method; Asymptotic distribution; Exponential distribution; R software
Source: Web Of Science
Added: August 6, 2018

2016 journal article

Exact prior-free probabilistic inference in a class of non-regular models

Stat, 5(1), 312–321.

By: R. Martin n & Y. Lin*

author keywords: conditioning; differential equation; inferential model; plausibility; validity
TL;DR: This paper constructs an inferential model (IM) framework for a class of highly non‐regular models with parameter‐dependent support and proves that the plausibility intervals derived from this IM are exact, and it is demonstrated that their exactness does not come at the cost of loss of efficiency. (via Semantic Scholar)
Source: Crossref
Added: August 16, 2021

2016 journal article

On an inferential model construction using generalized associations

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 195, 105–115.

By: R. Martin n

author keywords: Likelihood; Marginalization; Monte Carlo; Plausibility function; Random set; Validity
TL;DR: A particular variation on the IM construction is considered, one based on generalized associations, which is more flexible in that it does not require a complete specification of the data-generating process and is provably valid under mild conditions. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2015 journal article

A semiparametric scale-mixture regression model and predictive recursion maximum likelihood

Computational Statistics & Data Analysis, 94, 75–85.

By: R. Martin* & Z. Han n

author keywords: EM algorithm; Dirichlet process; Marginal likelihood; Nonparametric maximum likelihood; Normal scale mixture; Profile likelihood
TL;DR: A hybrid predictive recursion-EM algorithm is proposed for fitting flexible scale mixture model with a nonparametric mixing distribution that contains, among other things, the familiar normal and Student-t models as special cases. (via Semantic Scholar)
Sources: Crossref, Web Of Science
Added: August 6, 2018

2015 journal article

Prior-Free Probabilistic Prediction of Future Observations

Technometrics, 58(2), 225–235.

By: R. Martin* & R. Lingham*

author keywords: Disease count data; Environmental data; Inferential model; Plausibility; Prediction interval; System breakdown data; Validity
TL;DR: An IM-based technique is employed to marginalize out the unknown parameters, yielding prior-free probabilistic prediction of future observables, which is expected to be a useful tool for practitioners. (via Semantic Scholar)
Source: Crossref
Added: August 16, 2021

2014 journal article

Asymptotically Optimal Nonparametric Empirical Bayes Via Predictive Recursion

Communications in Statistics - Theory and Methods, 44(2), 286–299.

By: R. Martin*

author keywords: Batting average; Compound decision problem; Density estimation; High-dimensional; Mixture model
TL;DR: This article presents a general notion of empirical Bayes asymptotic optimality, and it is shown that PR-based procedures satisfy this property under certain conditions. (via Semantic Scholar)
Source: Crossref
Added: October 29, 2021

2014 journal article

Frameworks for prior-free posterior probabilistic inference

Wiley Interdisciplinary Reviews: Computational Statistics, 7(1), 77–85.

By: C. Liu* & R. Martin*

author keywords: Bayes; belief function; fiducial; inferential models; statistical principles
TL;DR: It is argued that Fisher's fiducial and its various extensions are not prior-free and, therefore, do not meet the requirements for prior‐free probabilistic inference, and the inferential model (IM) framework is shown to be a promising new method for generating both valid and efficient probabilism inference. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Crossref
Added: October 29, 2021

2014 journal article

Marginal Inferential Models: Prior-Free Probabilistic Inference on Interest Parameters

Journal of the American Statistical Association, 110(512), 1621–1631.

By: R. Martin* & C. Liu

author keywords: Belief; Efficiency; Nuisance parameter; Plausibility; Predictive random set; Validity
TL;DR: It is shown that this approach provides exact and efficient marginal inference in several challenging problems, including a many-normal-means problem, and a generalized marginalization technique is proposed and proved its validity. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Source: Crossref
Added: October 29, 2021

2014 journal article

Plausibility Functions and Exact Frequentist Inference

Journal of the American Statistical Association, 110(512), 1552–1561.

By: R. Martin*

author keywords: Bootstrap; Confidence region; Hypothesis test; Likelihood; Monte Carlo; p-Value; Profile likelihood
TL;DR: This article presents a general framework for the construction of exact frequentist procedures based on plausibility functions and shows that the plausibility function-based tests and confidence regions have the desired frequentist properties in finite samples. (via Semantic Scholar)
Source: Crossref
Added: October 29, 2021

2013 journal article

An Approximate Bayesian Marginal Likelihood Approach for Estimating Finite Mixtures

Communications in Statistics - Simulation and Computation, 42(7), 1533–1548.

By: R. Martin*

author keywords: Dirichlet distribution; Mixture complexity; Predictive recursion; Simulated annealing; Stochastic approximation
TL;DR: A computationally efficient stochastic approximation version of the marginal likelihood is proposed and large-sample theory is presented by restricting the support to a finite grid, and a simulated annealing method is employed to maximize themarginal likelihood and estimate the support. (via Semantic Scholar)
Source: Crossref
Added: October 29, 2021

2013 journal article

Correction

Journal of the American Statistical Association, 108(503), 1138–1139.

By: R. Martin* & C. Liu*

Source: Crossref
Added: October 29, 2021

2013 journal article

Inferential Models: A Framework for Prior-Free Posterior Probabilistic Inference

Journal of the American Statistical Association, 108(501), 301–313.

By: R. Martin* & C. Liu*

author keywords: Belief function; Plausibility function; Predictive random set; Score function; Validity
TL;DR: A new framework for probabilistic inference, based on inferential models (IMs), is presented, which not only provides data-dependent Probabilistic measures of uncertainty about the unknown parameter, but also does so with an automatic long-run frequency-calibration property. (via Semantic Scholar)
Source: Crossref
Added: October 29, 2021

2013 journal article

Random Sets and Exact Confidence Regions

Sankhya A, 76(2), 288–304.

By: R. Martin*

author keywords: Coverage probability; inferential model; plausibility function; predictive random set; validity
TL;DR: This paper describes a new approach, using random sets, which allows users to construct exact confidence regions without appeal to asymptotic theory, if the user-specified random set satisfies a certain validity property. (via Semantic Scholar)
Source: Crossref
Added: October 29, 2021

2012 journal article

On ε-Optimality of the Pursuit Learning Algorithm

Journal of Applied Probability, 49(03), 795–805.

By: R. Martin* & O. Tilak*

Source: Crossref
Added: October 29, 2021

2011 journal article

Convergence rate for predictive recursion estimation of finite mixtures

Statistics & Probability Letters, 82(2), 378–384.

By: R. Martin*

author keywords: Density estimation; Kullback-Leibler divergence; Lyapunov function; Mixture model; Stochastic approximation
Source: Crossref
Added: October 29, 2021

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