Christian Robert

Q: What Schools Are Affiliated With Christian Robert

Christian Robert is affiliated with the following schools: University of Warwick, Paris Sciences et Lettres University, Sorbonne University

Christian Robert's AcademicInfluence.com Rankings

Christian Robert

Mathematics

#3397

World Rank

#5020

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Statistics

#154

World Rank

#200

Historical Rank

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Mathematics

Why Is Christian Robert Influential?

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According to Wikipedia, Christian P. Robert is a French statistician, specializing in Bayesian statistics and Monte Carlo methods. Career Christian Robert studied at ENSAE then defended his PhD in 1987 at Université de Rouen. He held temporary positions at Purdue and Cornell before being an Associate Professor at Université Paris 6, and then Professor at Université de Rouen. He was also Professor of Statistics at École Polytechnique and director of Center for Research in Economics and Statistics. As of 2021, he is Professor at CEREMADE, Université Paris-Dauphine and a part-time member of the Department of Statistics, University of Warwick.

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Christian Robert's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Monte Carlo Statistical Methods (2005) (4501)
Monte Carlo Statistical Methods (Springer Texts in Statistics) (2005) (1303)
The Bayesian choice : from decision-theoretic foundations to computational implementation (2007) (1255)
The Bayesian choice (1994) (1197)
Bayesian Modeling Using WinBUGS (2009) (1065)
Statistics for Spatio-Temporal Data (2014) (1045)
Estimation of Finite Mixture Distributions Through Bayesian Sampling (1994) (967)
Deviance information criteria for missing data models (2006) (872)
Approximate Bayesian computational methods (2011) (790)
Discussion of "Sure independence screening for ultra-high dimensional feature space" by Fan and Lv. (2008) (765)
Superintelligence: Paths, Dangers, Strategies (2017) (710)
Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation (2008) (693)
Computational and Inferential Difficulties with Mixture Posterior Distributions (2000) (690)
Rao-Blackwellisation of sampling schemes (1996) (629)
An overview of robust Bayesian analysis (1994) (596)
Adaptive approximate Bayesian computation (2008) (587)
Abandon Statistical Significance (2017) (581)
Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (2012) (533)
Simulation of truncated normal variables (2009) (525)
Bayesian Modelling and Inference on Mixtures of Distributions (2005) (498)
Statistical Rethinking (2017) (448)
Introducing Monte Carlo Methods with R (2009) (401)
Bayesian Core: A Practical Approach to Computational Bayesian Statistics (2010) (369)
The Bayesian choice : a decision-theoretic motivation (1996) (337)
Lack of confidence in approximate Bayesian computation model choice (2011) (311)
Adaptive importance sampling in general mixture classes (2007) (298)
Sure independence screening for ultrahigh dimensional feature space Discussion (2008) (297)
Reliable ABC model choice via random forests (2014) (273)
A Short History of Markov Chain Monte Carlo: Subjective Recollections from Incomplete Data (2008) (251)
Adaptive Multiple Importance Sampling (2009) (241)
Estimating Mixtures of Regressions (2003) (233)
Inference in model-based cluster analysis (1997) (212)
Bayesian estimation of hidden Markov chains: a stochastic implementation (1993) (196)
Machine Learning, a Probabilistic Perspective (2014) (190)
Optimal Sample Size for Multiple Testing (2004) (173)
ABC likelihood-free methods for model choice in Gibbs random fields (2008) (172)
In defence of model‐based inference in phylogeography (2010) (170)
Reversible jump, birth‐and‐death and more general continuous time Markov chain Monte Carlo samplers (2003) (164)
Mixtures of Distributions: Inference and Estimation (1996) (163)
Bayesian computation: a summary of the current state, and samples backwards and forwards (2015) (162)
ABC random forests for Bayesian parameter inference (2016) (148)
Relevant statistics for Bayesian model choice (2011) (145)
MCMC Convergence Diagnostics : A « Reviewww » (1998) (140)
Optimal Sample Size for Multiple Testing : the Case of Gene Expression Mi roarraysPeter (2004) (139)
Understanding Computational Bayesian Statistics (2009) (133)
Convergence of adaptive mixtures of importance sampling schemes (2007) (131)
Evidence and Evolution: The logic behind the science (2011) (129)
Convergence Control Methods for Markov Chain Monte Carlo Algorithms (1995) (126)
The Metropolis–Hastings Algorithm (2015) (124)
Discussion on the paper by Spiegelhalter, Best, Carlin and van der Linde (2002) (124)
Harold Jeffreys’s Theory of Probability Revisited (2008) (122)
Bayesian-Optimal Design via Interacting Particle Systems (2006) (114)
Estimation of Accuracy in Testing (1992) (114)
Properties of nested sampling (2008) (113)
Convergence of Adaptive Sampling Schemes (2007) (112)
Mixtures: Estimation and Applications (2011) (110)
Generalized Accept-Reject sampling schemes (2004) (107)
Marginal maximum a posteriori estimation using Markov chain Monte Carlo (2002) (104)
Controlled MCMC for Optimal Sampling (2001) (104)
Model choice in generalised linear models: A Bayesian approach via Kullback-Leibler projections (1998) (103)
Minimum variance importance sampling via Population Monte Carlo (2007) (102)
Estimation of demo‐genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics (2012) (101)
Accelerating MCMC algorithms (2018) (93)
Approximate Bayesian computation with the Wasserstein distance (2019) (92)
Handbook of Mixture Analysis (2018) (91)
Bayesian estimation of switching ARMA models (1999) (87)
Asymptotic properties of approximate Bayesian computation (2016) (82)
On parameter estimation with the Wasserstein distance (2017) (82)
Bayesian Ideas and Data Analysis (2012) (77)
Bayesian computation via empirical likelihood (2012) (77)
Testing hypotheses via a mixture estimation model (2014) (75)
Bayesian Estimation of Small Effects in Exercise and Sports Science (2016) (74)
Inference in generative models using the Wasserstein distance (2017) (72)
Bayesian computational methods (2010) (70)
Discretization and Mcmc Convergence Assessment (1998) (70)
Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data (2014) (70)
Computational Advances for and from Bayesian Analysis (2004) (68)
Reparameterization strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation (1998) (68)
Computational methods for Bayesian model choice (2009) (65)
Explaining the Perfect Sampler (2001) (65)
Variable selection in qualitative models via an entropic explanatory power (2003) (65)
Bayesian Essentials with R (2013) (64)
Using Parallel Computation to Improve Independent Metropolis–Hastings Based Estimation (2010) (63)
On the Jeffreys-Lindley Paradox (2014) (63)
Introducing Monte Carlo Methods with R (Use R) (2009) (62)
Better together? Statistical learning in models made of modules (2017) (62)
Importance sampling methods for Bayesian discrimination between embedded models (2009) (60)
Stochastic Modelling for Systems Biology (second edition) (2012) (58)
Robust shrinkage estimators of the location parameter for elliptically symmetric distributions (1989) (57)
Monte Carlo Methods (2016) (56)
Bayesian computation for statistical models with intractable normalizing constants (2008) (55)
Subjective Hierarchical Bayes Estimation of a Multivariate Normal Mean: On the Frequentist Interface (1990) (54)
Lack of confidence in ABC model choice (2011) (54)
Reversible Jump MCMC Converging to Birth-and-Death MCMC and More General Continuous Time Samplers (2001) (53)
Bayesian model comparison in cosmology with Population Monte Carlo (2009) (53)
Accelerating Metropolis-Hastings algorithms by Delayed Acceptance (2015) (53)
Bayesian Inference on Mixtures of Distributions (2008) (51)
Intrinsic losses (1996) (50)
A Bayesian Reassessment of Nearest-Neighbor Classification (2008) (49)
Convergence Controls for MCMC Algorithms with Applications to Hidden Markov Chains (1999) (49)
Regularization in regression: comparing Bayesian and frequentist methods in a poorly informative situation (2010) (47)
Iterated importance sampling in missing data problems (2006) (46)
Mixture models, latent variables and partitioned importance sampling (2004) (46)
Many perspectives on Deborah Mayo's "Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars" (2019) (46)
Modified Bessel functions and their applications in probability and statistics (1990) (46)
The expected demise of the Bayes factor (2015) (46)
Estimation of noncentrality parameters (1993) (45)
The Seven Pillars of Statistical Wisdom (2018) (44)
Model misspecification in approximate Bayesian computation: consequences and diagnostics (2020) (44)
A vanilla Rao--Blackwellization of Metropolis--Hastings algorithms (2009) (44)
A mixture representation of π with applications in Markov chain Monte Carlo and perfect sampling (2004) (43)
On some difficulties with a posterior probability approximation technique (2008) (42)
A Mixture Approach to Bayesian Goodness of Fit (2002) (41)
Is Pitman Closeness a Reasonable Criterion (1993) (41)
Rethinking the Effective Sample Size (2018) (41)
New Perspectives on Linear Calibration (1994) (40)
On Bayesian Data Analysis (2010) (40)
Logicomix: An Epic Search for Truth (2012) (40)
Reparameterisation issues in mixture modelling and their bearing on MCMC algorithms (1999) (40)
Markov Chain Monte Carlo: 10 Years and Still Running! (2000) (40)
Pre-processing for approximate Bayesian computation in image analysis (2014) (38)
MCMC Control Spreadsheets for Exponential Mixture Estimation (1999) (37)
Naked Statistics: Stripping the Dread from Data (2014) (36)
Magical Mathematics: The Mathematical Ideas That Animate Great Magic Tricks (2013) (35)
Perfect simulation of positive Gaussian distributions (2003) (34)
Model Selection for Mixture Models – Perspectives and Strategies (2018) (34)
Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models (2016) (34)
On resolving the Savage–Dickey paradox (2009) (33)
Refining Poisson Confidence Intervals (1988) (31)
Tooling (2019) (31)
Post-Processing Accept-Reject Samples: Recycling and Rescaling (1998) (31)
Perfect Slice Samplers for Mixtures of Distributions (1999) (30)
Linking theory and practice of MCMC. (2003) (30)
Approximate Bayesian Computation: A Survey on Recent Results (2014) (30)
On perfect simulation for some mixtures of distributions (1999) (29)
Expectation Propagation as a Way of Life (2020) (29)
A Paradox in Decision-Theoretic Interval Estimation (1990) (28)
ABC model choice via random forests (2014) (27)
On Particle Learning (2010) (27)
“Not Only Defended But Also Applied”: The Perceived Absurdity of Bayesian Inference (2010) (26)
Improving the Convergence Properties of the Data Augmentation Algorithm with an Application to Bayesian Mixture Modeling (2009) (26)
ABC methods for model choice in Gibbs random fields (2008) (26)
Introducing Monte Carlo methods with (2013) (25)
Revised evidence for statistical standards (2014) (25)
Confidence bands for Brownian motion and applications to Monte Carlo simulation (2007) (25)
Model Misspecification in ABC: Consequences and Diagnostics (2017) (25)
Riemann sums for MCMC estimation and convergence monitoring (2001) (24)
Intrinsic credible regions : On objective Bayesian approach to interval estimation (2006) (24)
ESTIMATION OF QUADRATIC FUNCTIONS: NONINFORMATIVE PRIORS FOR NON-CENTRALITY PARAMETERS (1998) (23)
Discretization of Continuous Markov Chains and Markov Chain Monte Carlo Convergence Assessment (1998) (23)
Generalized Bouncy Particle Sampler (2017) (23)
CosmoPMC: Cosmology Population Monte Carlo (2011) (22)
Maximum likelihood estimation under order restrictions by the prior feedback method (1996) (22)
On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models (2002) (22)
Contemplating Evidence: properties, extensions of, and alternatives to Nested Sampling (2008) (22)
Likelihood-Free Model Choice (2015) (22)
Generalized inverse normal distributions (1991) (22)
Introduction to Special Issue on Monte Carlo Methods in Statistics (2013) (21)
Coordinate sampler: a non-reversible Gibbs-like MCMC sampler (2018) (21)
Using a Markov Chain to Construct a Tractable Approximation of an Intractable Probability Distribution (2006) (21)
Approximating the marginal likelihood in mixture models (2008) (20)
Componentwise approximate Bayesian computation via Gibbs-like steps (2019) (20)
Monte Carlo Integration (2010) (20)
Bayesian computation: a perspective on the current state, and sampling backwards and forwards (2015) (19)
Incoherent phylogeographic inference (2010) (19)
The Most Human Human (2014) (19)
Eaton's Markov chain, its conjugate partner and P-admissibility (1999) (19)
Dicussion on the meeting on ‘Statistical approaches to inverse problems’ (2004) (18)
Three discussions of the paper "sequential quasi-Monte Carlo sampling", by M. Gerber and N. Chopin (2015) (18)
The Simulated Likelihood Ratio (SLR) Method (1998) (18)
On the Jeffreys-Lindley's paradox (2013) (17)
Are Risk Averse Agents More Optimistic? A Bayesian Estimation Approach (2007) (17)
Convergence Control of MCMC Algorithms (1998) (17)
Approximate Bayesian Computation in State Space Models (2014) (16)
Independent Random Sampling Methods (2019) (16)
Computational Solutions for Bayesian Inference in Mixture Models (2018) (15)
Bayesian Inference in Hidden Markov Models through Jump Markov Chain Monte Carlo (1999) (14)
Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin (2010) (14)
On some accurate bounds for the quantiles of a non-central chi squared distribution☆ (1990) (14)
A note on the confidence properties of reference priors for the calibration model (1998) (13)
Computing Bayes: Bayesian Computation from 1763 to the 21st Century (2020) (13)
Bayesian mixture models in a longitudinal setting for analysing sheep CAT scan images (2007) (13)
Accelerating Metropolis-Hastings algorithms: Delayed acceptance with prefetching (2014) (13)
Why approximate Bayesian computational (ABC) methods cannot handle model choice problems (2011) (13)
Report of the Editors—2009 (2010) (13)
Jeffreys priors for mixture estimation: Properties and alternatives (2017) (12)
Bayesian Inference on Finite Mixtures of Distributions (2009) (12)
Approximating the likelihood in approximate Bayesian computation (2018) (12)
Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale (2018) (12)
Improved Confidence Sets in Spherically Symmetric Distributions (1987) (12)
Model choice versus model criticism (2009) (12)
Importance Sampling Schemes for Evidence Approximation in Mixture Models (2013) (11)
Noninformative Bayesian testing and neutral Bayes factors (1996) (11)
Bayesian Computational Tools (2013) (11)
Discussion: Markov Chains for Exploring Posterior Distributions (1994) (11)
On variance stabilisation in Population Monte Carlo by double Rao-Blackwellisation (2010) (11)
Reading Keynes' Treatise on Probability (2010) (11)
Medical Illuminations: Using Evidence, Visualization and Statistical Thinking to Improve Healthcare (2014) (11)
Approximating the Likelihood in ABC (2018) (11)
Measuring Statistical Evidence Using Relative Belief (2016) (11)
Jeffreys priors for mixture estimation (2015) (11)
Integral equation solutions as prior distributions for Bayesian model selection (2008) (10)
An introduction to the special issue “Joint IMS-ISBA meeting - MCMSki 4” (2015) (10)
Introduction to the Special Issue: Bayes Then and Now (2004) (10)
Estimation of a normal mixture model through Gibbs sampling and Prior Feedback (1993) (10)
Approximate Bayesian computation via empirical likelihood (2012) (10)
Loss Functions for Set Estimations (1994) (10)
Efficient learning in ABC algorithms (2012) (10)
Connectedness conditions for the convergence of the Gibbs sampler (1997) (10)
An Explicit Formula for the Risk of the Positive‐Part James‐Stein Estimator (1988) (9)
Are risk agents more optimistic? A Bayesian estimation approach (2008) (9)
Numerical Analysis for Statisticians, Second Edition by Kenneth Lange (2011) (9)
Distance weighted losses for testing and confidence set evaluation (1994) (9)
On the Relevance of the Bayesian Approach to Statistics (2009) (8)
James E. Gentle: Computational statistics (Statistics and Computing Series) (2011) (8)
Improved Confidence Estimators for the Usual Multivariate Normal Confidence Set (1989) (8)
Simulating Nature (2012) (8)
Brownian confidence bands on Monte Carlo output (2004) (8)
Improved Confidence Statements for the Usual Multivariate Normal Confidence Set (1994) (8)
Estimation of a non-centrality parameter under Stein-type-like losses (2000) (7)
Discussion of "Is Bayes Posterior just Quick and Dirty Confidence?" by D. A. S. Fraser (2011) (7)
In Pursuit of the Unknown: 17 Equations That Changed the World (2013) (7)
Statistics Done Wrong: The Woefully Complete Guide (2016) (7)
Rejoinder: Harold Jeffreys’s Theory of Probability Revisited (2009) (7)
Simulation in statistics (2011) (7)
Population Monte Carlo for Ion Channel Restoration (2002) (6)
THE SIMULATED LIKELIHOOD RATIO METHOD (2002) (6)
Reflecting about Selecting Noninformative Priors (2014) (6)
Integrated objective Bayesian estimation and hypothesis testing : a discussion (2010) (6)
A vanilla RaoBlackwellization of MetropolisHastings algorithms (2011) (6)
Rao-Blackwellization in the MCMC era (2021) (6)
Monte Carlo Optimization (2010) (5)
Metropolis–Hastings Algorithms (2010) (5)
Monte Carlo algorithms for model assessment via conflicting summaries (2011) (5)
Bayesian Essentials with R (2nd ed.) (2014) (5)
Estimation of Exponential Mixtures (1998) (5)
MCMC Specifics for Latent Variable Models (1998) (5)
On Consistency of Approximate Bayesian Computation (2015) (5)
Control by the Central Limit Theorem (1998) (5)
Weakly Informative Reparameterizations for Location-Scale Mixtures (2016) (5)
Subsampling Weakly Dependent Times Series and Application to Extremes (2010) (5)
The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy by Sharon Bertsch McGrayne (2012) (5)
Nested sampling for Bayesian computations: A discussion (2006) (4)
Some difficulties with some posterior probability approximations (2008) (4)
Monte Carlo Methods in Statistics (2009) (4)
Truth or Truthiness: Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist (2018) (4)
Decision-Theoretic Foundations (2007) (4)
Rao–Blackwellisation in the Markov Chain Monte Carlo Era (2021) (4)
Discretization and MCMC Convergence Assessment (Lecture Notes in Statistics Vol. 135) (1999) (4)
Bayesian model comparison in cosmology with Population (2010) (4)
Markov Chain Monte Carlo Methods, Survey with Some Frequent Misunderstandings (2020) (4)
Capture-Recapture Models and Bayesian Sampling (1990) (4)
ABC Methods for Bayesian Model Choice (2011) (4)
Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation" (2012) (4)
R For Dummies (2013) (4)
On variance stabilisation by double Rao-Blackwellisation (2008) (4)
Marginal MAP estimation using Markov chain Monte Carlo (1999) (4)
Discussion on the paper by Brooks, Giudici and Roberts (2003) (4)
Average of Recentered Parallel MCMC for Big Data (2017) (4)
Is Pitman Closeness a Reasonable Criterion?: Rejoinder (1993) (3)
Discussions on "Riemann manifold Langevin and Hamiltonian Monte Carlo methods" (2010) (3)
Pragmatics of Uncertainty (2019) (3)
Comment on article by Jain and Neal (2007) (3)
Invertible Flow Non Equilibrium sampling (2021) (3)
The Multi-Stage Gibbs Sampler (2004) (3)
Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig (2017) (3)
Bayesian Inference and Computation (2011) (3)
Bayesian Point Estimation (2007) (3)
Convergence Monitoring and Adaptation for MCMC Algorithms (2010) (3)
Parallelising MCMC via Random Forests (2019) (3)
How Principled and Practical Are Penalised Complexity Priors (2017) (3)
Non-informative reparameterisations for location-scale mixtures (2016) (3)
Prime Suspects (2019) (3)
Objective Bayesian hypothesis testing in binomial regression models with integral prior distributions (2013) (3)
Discussion on the paper by Wakefield (2004) (3)
Controlled shrinkage estimators (a class of estimators better than the least squares estimator, with respect to a general quadratic loss, for normal observations (1989) (3)
A Wealth of Numbers (2012) (3)
Linking Discrete and Continuous Chains (1998) (3)
Recycling rejected values in accept-reject methods (1995) (3)
Application of ABC to Infer the Genetic History of Pygmy Hunter-Gatherer Populations from Western Central Africa (2018) (3)
Choice Among Hypotheses Using Estimation Criteria (1997) (3)
BAYESIAN ANALYSIS WITH APPLICATION TO THE TIMING RESIDUALS OF A PULSAR (1999) (3)
Approximating Bayes in the 21st Century (2021) (3)
Paradoxes in Scientific Inference (2013) (3)
Search of a gravitational wave background in timing residuals of PSR 1937 + 21: minimal model and upper limits on Ωgr (1997) (2)
Book Reviews (2014) (2)
Comments on Particle Markov chain Monte Carlo" by C. Andrieu, A. Doucet, and R. Hollenstein" (2009) (2)
On computational tools for Bayesian data analysis (2010) (2)
Big Bayes Stories—Foreword (2014) (2)
Foundations of Statistical Algorithms (2014) (2)
From Prior Information to Prior Distributions (2007) (2)
Intrinsic losses for empirical Bayes estimation: A note on normal and Poisson cases (1995) (2)
Bayesian hypothesis testing as a mixture estimation modelT1 (2021) (2)
The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff (2012) (2)
MINIMUM VARIANCE IMPORTANCE SAMPLING VIA POPULATION MONTE (2007) (2)
Two discussions of the paper "Bayesian measures of model complexity and fit" by D. Spiegelhalter et al., Read before The Royal Statistical Society at a meeting organized by the Research Section on Wednesday, March 13th, 2002 (2013) (2)
Errors, Blunders, and Lies (2018) (2)
In praise of the referee (2012) (2)
Computing Bayes: From Then ‘Til Now (2022) (2)
Is that a big number? (2019) (2)
The Two-Stage Gibbs Sampler (2004) (2)
Handbook of Fitting Statistical Distributions with R by Zaven A. Karian, Edward J. Dudewicz (2012) (2)
A MCMC approach to maximum likelihood estimation (1998) (2)
A discussion on: Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations by Rue, H. Martino, S. and Chopin, N. (2009) (2)
Nonoptimality of Randomized Confidence Sets (1988) (2)
Harold Jeffreys' Theory of Probability revisited: a reply (2009) (2)
Do we need an integrated Bayesian/likelihood inference? (2010) (2)
A Pathological MCMC Algorithm and its Use as a Benchmark for Convergence Assessment Techniques (1998) (2)
The Search for Certainty: A Critical Assessment (2010) (2)
Interview with: Persi Diaconis (2012) (2)
Random Variable Generation (2010) (2)
Variable Dimension Models and Reversible Jump Algorithms (2004) (2)
A Comparison of the Bayesian and Frequentist Approaches to Estimation by Francisco J. Samaniego (2011) (2)
10th International Workshop on Simulation and Statistics (2019) (2)
The Universe in Zero Words (2012) (1)
The Gibbs Sampler (1999) (1)
Statistical Modeling and Computation (2014) (1)
First moments of the truncated and absolute Student's variates (2011) (1)
Some comments about A Bayesian criterion for singular models by M. Drton and M. Plummer (2016) (1)
Rao-Blackwellization of Generalized Accept-Reject Schemes (2000) (1)
Error and inference: an outsider stand on a frequentist philosophy (2011) (1)
Point Estimation and Confidence Set in a Parallelism Model: an Empirical Bayes Approach (1991) (1)
Markov Chain Monte Carlo Algorithms for Bayesian Computation, a Survey and Some Generalisation (2020) (1)
THE SIMULATED LIKELIHOOD RATIO ( SLR ) METHODM (1998) (1)
Basic R Programming (2010) (1)
Comments on "Confidence distribution, the frequentist distribution estimator of a parameter --- a review" by Min-ge Xie and Kesar Singh (2012) (1)
Maximum a Posteriori Parameter Estimation for Hidden Markov Models (2000) (1)
One Perfect Simulation for some Mixture of Distributions (1998) (1)
Computational Methods for Numerical Analysis with R (2019) (1)
A lower bound for the risk of classes of shrinkage estimators ina general multivariate estimation problem and some deduced estimators (1989) (1)
Minimum variance importance sampling via Population (2005) (1)
A Handbook of Statistical Analyses Using R, Second Edition by Brian S. Everitt, Torsten Hothorn (2011) (1)
The Slice Sampler (2004) (1)
Introducing Monte Carlo Methods with R Solutions to Odd-Numbered Exercises (2010) (1)
Some comments about James Watson's and Chris Holmes' "Approximate Models and Robust Decisions" (2016) (1)
The Cartoon Introduction to Statistics (2014) (1)
Moralizing perfect sampling (2001) (1)
Regression and Variable Selection (2014) (1)
Rejoinder: The Anti-Bayesian Moment and Its Passing (2013) (1)
Evidence and Evolution: A Review (2010) (1)
Admissibility and Complete Classes (2007) (1)
BAYESIAN COMPUTATIONAL TOOLS: A BRIEF TUTORIAL (2006) (1)
Statistics and Analysis of Scientific Data (Second Edition) (2021) (1)
Controling Monte Carlo Variance (2004) (1)
Estimating the integrated likelihood via posterior simulation using the harmonic mean equality: A discussion (2006) (1)
Evaluating statistic appropriateness for Bayesian model choice (2011) (1)
The Foundations of Statistics: A Simulation‐Based Approach by Shravan Vasishth, Michael Broe (2011) (1)
Reading Theorie Analytique des Probabilites (2012) (1)
APPROXIMATE BAYESIAN COMPUTATION, AN INTRODUCTION (2020) (1)
Are risk averse agents more optimistic (2005) (1)
Exact Bayesian Analysis of Mixtures (2010) (1)
Issues in Designing Hybrid Algorithms (2011) (1)
Discussion on the paper by Kong, McCullagh, Meng, Nicolae and Tan (2003) (1)
Nonparametric Bayesian Clay for Robust Decision Bricks (2016) (1)
The Importance Markov Chain (2022) (1)
Valid Discretization via Renewal Theory (1998) (1)
Capture–Recapture Experiments (2014) (1)
The 9 Pitfalls of Data Science (2020) (1)
AIQ (2019) (1)
Some comments about A. Ronald Gallant's "Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference" (2015) (1)
Special Issue on George Casella's Books (2013) (1)
A discussion of \Bayesian model selection based on proper scoring rules" by A.P. Dawid and M. Musio (2015) (1)
Computing Bayes: From Then ‘Til Now 1 (2022) (0)
Sampling using Adaptive Regenerative Processes (2022) (0)
Bayesian Essentials With R 2nd Edition (2020) (0)
Comment on: Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference (2016) (0)
n ° 2010-32 The Search for Certainty : A Critical Assessment (2010) (0)
The simulated Newton Raphson method (2001) (0)
Coordinate sampler: a non-reversible Gibbs-like MCMC sampler (2019) (0)
Bayesian Core: The Complete Solution Manual (2009) (0)
Une Vie Brève (One Hundred Twenty-One Days) (2017) (0)
Discussion on the paper "Sequential quasi Monte Carlo" by Gerber and Chopin (2015) (0)
Book Reviews (2011) (0)
50 shades of Bayesian testing of hypotheses (2022) (0)
Error and inference: an outsider stand on a frequentist philosophy (2012) (0)
A Whistle-Stop Tour of Statistics (2012) (0)
Approximate Bayesian computational methods (2011) (0)
Jeffreys Priors for Mixture Models (2014) (0)
Principles of Uncertainty (Second Edition) (2021) (0)
Comment on Article by Dawid and Musio (2015) (0)
Let the Evidence Speak (2019) (0)
Discussion (2002) (0)
Discussion (2013) (0)
Principles of Applied Statistics (2012) (0)
Quick(er) Calculations (2021) (0)
Living on the Edge: An Unified Approach to Antithetic Sampling (2021) (0)
2. Gaussian markov random fields: theory and applications. Håvard Rue and Leonhard Held, Chapman & Hall/CRC, Boca Raton, 2005. No. of pages: 280 (hardcover). Price: $79.95. ISBN: 1‐ 58488‐432‐0 (2006) (0)
Implementation in Missing Data Models (1999) (0)
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin and Guesstimation 2.0: Solving Today's Problems on the Back of a Napkin (2013) (0)
Some comments about "Penalising model component complexity" by Simpson et al. (2017) (2016) (0)
A correction of the bias in the ABC-PRC algorithm (2008) (0)
Poems that Solve Puzzles (2021) (0)
Bayes Estimators Associated with Uniform Distributions on Spheres (II): the Hierarchical Bayes Approach (1989) (0)
Casanova’s Lottery (2023) (0)
10 Great Ideas About Chance (2019) (0)
Approximate Bayesian Computation for model selection (2012) (0)
Hierarchical Bayesian Methods in Ecology (2010) (0)
\Not only defended but also applied": A look back at Feller's take on Bayesian inference (2010) (0)
Book reviews, Summer 2012, Principles of Applied Statistics (2012) (0)
Bayes Then and Now (2004) (0)
Practical Bayesian Inference: A Primer for Physical ScientistsCoryn A. L.Bailer‐JonesCambridge University Press, 2017, x + 295 pages, £69.99, hardcover ISBN 978‐1‐316‐64221‐4 (2019) (0)
Rao-Biackwellization of Sampling Schemes (2012) (0)
Bayes Factors for Forensic Decision Analyses with R (2023) (0)
Straightforward Statistics: Understanding the Tools of Research (2014) (0)
Accelerating Metropolis–Hastings algorithms by Delayed AcceptanceT1 (2018) (0)
What Makes Variables Random: Probability for the Applied Researcher (2018) (0)
Bayesian Inference (2010) (0)
Surprises in Probability–Seventeen Short Stories (2019) (0)
The Error of Truth (2021) (0)
Agreement of an electronic tube (2007) (0)
Generalized Poisson Difference Autoregressive Processes (2020) (0)
The Theory That Would Not Die: Hardcover: 320+xiv pages Publisher: Yale University Press (first edition, May 2011) Language: English ISBN-10: 0300169698 (2012) (0)
Controlling and Accelerating Convergence (2010) (0)
Tests and Confidence Regions (2007) (0)
A special issue on Bayesian inference: challenges, perspectives and prospects (2023) (0)
Bayesian Cost-Effectiveness Analysis of Medical Treatments (2020) (0)
3 Notes on Markov Chain Monte Carlo (0)
Bayes Rules! (2022) (0)
Essentials of Probability Theory for Statisticians (2020) (0)
Algorithm Theoretical Basis Document. GOMOS - AerGOM (2020) (0)
Learning Base R (2nd edition) (2022) (0)
Interactive stratigraphic modeling (1982) (0)
What Are the Chances? (Why We Believe in Luck) (2022) (0)
Fano Limits on Matching Bandwidth (2005) (0)
The anti-Bayesian moment and its passing (2012) (0)
Invariance, Haar Measures, and Equivariant Estimators (2007) (0)
A Discussion on " Sure Independence Screening for Ultrahigh Di- Mensional Feature Space " (0)
Book reviews, Winter 2012 (2012) (0)
Book reviews, Fall 2011 (2011) (0)
Bayesian computation: a summary of the current state, and samples backwards and forwards (2015) (0)
Time Series: Modeling, Computation, and Inference by Raquel Prado, Mike West: A review (2011) (0)
Iterated and Sequential Importance Sampling (2004) (0)
A Computational Approach to Statistical Learning (2020) (0)
C O ] 4 M ar 2 00 9 Estim ation ofcosm ologicalparam eters using adaptive im portance sam pling (2008) (0)
Birthdays in Spurts : Analyzing a Spike in a Random Sequence (2014) (0)
Animation en long sejour (1988) (0)
Pre-processing for approximate Bayesian computation in image analysis (2014) (0)
Bayesian Essentials with R: The Complete Solution Manual (2015) (0)
Bayesian Estimation of a Covariance Matrix: Application for Asset and Liabiliy Management (2010) (0)
Bayesian Model Selection and Statistical Modeling by Tomohiro Ando (2011) (0)
Bayesian modelling and inference difficulties on mixtures of distributions (2004) (0)
Discussion of two Papers Read at the Society Half-Day on Inverse Problems on December 10 th , 2003 (0)
An introduction to the special issue “Joint IMS-ISBA meeting - MCMSki 4” (2014) (0)
Decision-Theoretic Foundations of Statistical Inference (1994) (0)
Implementing the Markov Chain and Inferring about the Restored Sequence. A Discussion of "Accurate Restoration of DNA Sequences" by G. A. Churchill (1993) (0)
(2019). Accelerating Metropolis-Hastings algorithms by Delayed Acceptance. Foundations of Data Science , 1 (2), 103-128. (2019) (0)
Understanding Elections through Statistics: Polling, Prediction, and Testing (2021) (0)
On some di(cid:14)culties with a posterior probability approximation technique (2008) (0)
Bayesian computational methods (2e ed.) (2010) (0)
Bayesian Probability for Babies (2023) (0)
Editor’s note: 25th Anniversary Special Issue (2015) (0)
Book reviews, Spring 2013 . Special issue on George Casella's books (2012) (0)
Testing R Code (2018) (0)
About Incoherent Inference (2010) (0)
Book Reviews (Spring 2012) (2012) (0)
Beyond the Bayes Factor, A New Bayesian Paradigm for Handling Hypothesis Testing (2016) (0)
Jeffreys Priors for Mixture Models Distribuzioni a priori di Jeffreys per i modelli mistura (2014) (0)
Supplementary Appendix: Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models (2019) (0)
Principles of Uncertainty, by J.B. Kadane: A review (2012) (0)
Bayesian Model Selection and Statistical Modeling by Tomohiro Ando: A review (2011) (0)
Generalized Linear Models (1985) (0)
Evidence estimation in finite and infinite mixture models and applications (2022) (0)
Introduction to “Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields” by J. Stoehr, P. Pudlo, L. Cucala (2015) (0)
The Beauty of Mathematics in Computer Science (2019) (0)
Time Series: Modeling, Computation, and Inference by Raquel Prado, Mike West (2011) (0)
Introduction to “Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields” by J. Stoehr, P. Pudlo, L. Cucala (2014) (0)
A Defense of the Bayesian Choice (1994) (0)
Some comments about “ Penalising model component complexity : A principled , practical approach to constructing priors ” by Simpson , Rue , Martins , Riebler , and Sørbye (2016) (0)
Bayesian Analysis of Overdispersed Count Data with Application to Teletraffic Monitoring (1998) (0)
The Isba Bulletin a Last Message from the President a Message from the Editor (2008) (0)
Three discussions on model choice (2006) (0)
A Bayesian Generalized Poisson Model for Cyber Risk Analysis (2021) (0)
Hierarchical and Empirical Bayes Extensions (1994) (0)
Discussion on the paper of Gerber and Chopin "Quasi Monte Carlo" (2015) (0)
Bayesian Decision Analysis: Principles and Practice by Jim Q. Smith: A review (2011) (0)
SEMI-TAIL UPPER BOUNDS ON ADMISSIBLE ESTIMATORS IN CONTINUOUS EXPONENTIAL FAMILIES WITH A NUISANCE PARAMETER (1998) (0)
Book reviews, Summer 2012 (2012) (0)

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