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Relevant statistics for Bayesian model choice

Rousseau, Judith; Robert, Christian P.; Pillai, Natesh S.; … - Université Paris-Dauphine (Paris IX) - 2014

The choice of the summary statistics in Bayesian inference and in particular in ABC algorithms is paramount to produce a valid outcome. We derive necessary and sufficient conditions on those statistics for the corresponding Bayes factor to be convergent, namely to asymptotically select the true...

Persistent link: https://www.econbiz.de/10011166507

Understanding the Fine Structure of Electricity Prices

Geman, Hélyette; Roncoroni, Andréa - Université Paris-Dauphine (Paris IX) - 2006

This paper analyzes the special features of electricity spot prices derived from the physics of this commodity and from the economics of supply and demand in a market pool. Besides mean-reversion, a property they share with other commodities, power prices exhibit the unique feature of spikes in...

Persistent link: https://www.econbiz.de/10011166403

Robust outlier detection for Asia–Pacific stock index returns

Ané, Thierry; Ureche-Langau, Loredana; Gambet, Jean-Benoît - Université Paris-Dauphine (Paris IX) - 2008

Outliers can lead to model misspecifications, poor forecasts and invalid inferences. Their identification and correction is therefore an important objective of financial modeling. This paper introduces a simple method to detect outliers in a financial series. It uses an AR(1)–GARCH(1,1) model...

Persistent link: https://www.econbiz.de/10010752616

Studentization and deriving accurate p-values

Rousseau, Judith; Fraser, Donald - Université Paris-Dauphine (Paris IX) - 2008

Bayesian literature, with many variations and some preference for two versions labelled pppost and pcpred. The bootstrap method … develop: an ancillary based p-value designated panc; a special version of the Bayesian pcpred; and a bootstrap based p … bootstrap would require a magnitude more in computation and would perhaps not be accessible. Examples are given to indicate the …

Persistent link: https://www.econbiz.de/10010905315

Simulation in Statistics

Robert, Christian P. - Université Paris-Dauphine (Paris IX) - 2011

Simulation has become a standard tool in statistics because it may be the only tool available for analysing some classes of probabilistic models. We review in this paper simulation tools that have been specifically derived to address statistical challenges and, in particular, recent advances in...

Persistent link: https://www.econbiz.de/10010707776

Explaining the Perfect Sampler

Casella, George; Lavine, Michael; Robert, Christian P. - Université Paris-Dauphine (Paris IX) - 2001

In 1996, Propp and Wilson introduced coupling from the past (CFTP), an algorithm for generating a sample from the exact stationary distribution of a Markov chain. In 1998, Fill proposed another so–called perfect sampling algorithm. These algorithms have enormous potential in Markov Chain Monte...

Persistent link: https://www.econbiz.de/10011162138

A Probabilistic Numerical Method for Fully Nonlinear Parabolic PDEs

Fahim, Arash; Touzi, Nizar; Warin, Xavier - Université Paris-Dauphine (Paris IX) - 2011

We consider the probabilistic numerical scheme for fully nonlinear PDEs suggested in [12], and show that it can be introduced naturally as a combination of Monte Carlo and finite differences scheme without appealing to the theory of backward stochastic differential equations. Our first main...

Persistent link: https://www.econbiz.de/10011166473

Reversible jump, birth-and-death and more general continuous time Markov chain Monte Carlo samplers

Cappé, Olivier; Robert, Christian P.; Ryden, Tobias - Université Paris-Dauphine (Paris IX) - 2003

Reversible jump methods are the most commonly used Markov chain Monte Carlo tool for exploring variable dimension statistical models. Recently, however, an alternative approach based on birth-and-death processes has been proposed by Stephens for mixtures of distributions. We show that the...

Persistent link: https://www.econbiz.de/10011166499

SMC^2: an efficient algorithm for sequential analysis of state-space models

Chopin, Nicolas; Jacob, Pierre E.; Papaspiliopoulos, Omiros - Université Paris-Dauphine (Paris IX) - 2013

We consider the generic problem of performing sequential Bayesian inference in a state-space model with observation process y, state process x and fixed parameter theta. An idealized approach would be to apply the iterated batch importance sampling (IBIS) algorithm of Chopin (2002). This is a...

Persistent link: https://www.econbiz.de/10011166506

The Wang-Landau algorithm reaches the Flat Histogram criterion in finite time

Jacob, Pierre E.; Ryder, Robin - Université Paris-Dauphine (Paris IX) - 2014

The Wang-Landau algorithm aims at sampling from a probability distribution, while penalizing some regions of the state space and favouring others. It is widely used, but its convergence properties are still unknown. We show that for some variations of the algorithm, the Wang-Landau algorithm...

Persistent link: https://www.econbiz.de/10011166535