Publications associées à Asymptotic theory (statistics)

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Frequency domain theory for functional time series: Variance decomposition and an invariance principle

Neda Mohammadi Jouzdani

This paper is concerned with frequency domain theory for functional time series, which are temporally dependent sequences of functions in a Hilbert space. We consider a variance decomposition, which is more suitable for such a data structure than the varia ...

INT STATISTICAL INST2020

High-Frequency Analysis Of Parabolic Stochastic Pdes

Carsten Hao Ye Chong

We consider the problem of estimating stochastic volatility for a class of second-order parabolic stochastic PDEs. Assuming that the solution is observed at high temporal frequency, we use limit theorems for multipower variations and related functionals to ...

INST MATHEMATICAL STATISTICS2020

Multivariate extremes over a random number of observations

Simone Padoan, Stefano Rizzelli

The classical multivariate extreme-value theory concerns the modeling of extremes in a multivariate random sample, suggesting the use of max-stable distributions. In this work, the classical theory is extended to the case where aggregated data, such as max ...

WILEY2020

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Michel Bierlaire, Prateek Bansal

Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to Markov chain Monte Carlo (MCMC) methods for scalable Bayesian estimation of mixed multinomial logit (MMNL) models. It has been established that VB is substan ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Recovering covariance from functional fragments

Victor Panaretos, Marie-Hélène Descary

We consider nonparametric estimation of a covariance function on the unit square, given a sample of discretely observed fragments of functional data. When each sample path is observed only on a subinterval of length , one has no statistical information on ...

2019

Mirrored Langevin Dynamics

Volkan Cevher, Paul Thierry Yves Rolland, Ya-Ping Hsieh, Ali Kavis

We consider the problem of sampling from constrained distributions, which has posed significant challenges to both non-asymptotic analysis and algorithmic design. We propose a unified framework, which is inspired by the classical mirror descent, to derive ...

2018

Mirrored Langevin Dynamics

Volkan Cevher, Paul Thierry Yves Rolland, Ya-Ping Hsieh, Ali Kavis

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

On the distribution of squarefree integers in arithmetic progressions

Pierre Francis André Le Boudec

investigate the error term of the asymptotic formula for the number of squarefree integers up to some bound, and lying in some arithmetic progression a (mod q). In particular, we prove an upper bound for its variance as a varies over (Z/qZ)(x) which consid ...

SPRINGER HEIDELBERG2018

Dependence properties of spatial rainfall extremes and areal reduction factors

Anthony Christopher Davison, Sebastian Engelke

Areal reduction factors (ARFs) transform an estimate of extreme rainfall at a point to an estimate of extreme rainfall over a spatial domain, and are commonly used in flood risk estimation. For applications such as the design of large infrastructure, dam s ...

2018

Asymptotic theory (statistics)

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Frequency domain theory for functional time series: Variance decomposition and an invariance principle

High-Frequency Analysis Of Parabolic Stochastic Pdes

Multivariate extremes over a random number of observations

Bootstrapping massive quantum field theories

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Recovering covariance from functional fragments

Mirrored Langevin Dynamics

Mirrored Langevin Dynamics

On the distribution of squarefree integers in arithmetic progressions

Dependence properties of spatial rainfall extremes and areal reduction factors

Multivariate extremes over a random number of observations

Bootstrapping massive quantum field theories

Frequency domain theory for functional time series: Variance decomposition and an invariance principle

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Mirrored Langevin Dynamics

Mirrored Langevin Dynamics

On the distribution of squarefree integers in arithmetic progressions

Dependence properties of spatial rainfall extremes and areal reduction factors

High-Frequency Analysis Of Parabolic Stochastic Pdes

Recovering covariance from functional fragments