Personne
Victor Panaretos
Publications associées (42)
On distributional autoregression and iterated transportation
Victor Panaretos, Laya Ghodrati
We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...
Hoboken2024Transportation-based functional ANOVA and PCA for covariance operators
Victor Panaretos, Yoav Zemel, Valentina Masarotto
We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...
Inst Mathematical Statistics-Ims2024Functional data analysis with rough sample paths?
Victor Panaretos, Neda Mohammadi Jouzdani
Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...
TAYLOR & FRANCIS LTD2023Detecting whether a stochastic process is finitely expressed in a basis
Victor Panaretos, Neda Mohammadi Jouzdani
Is it possible to detect if the sample paths of a stochastic process almost surely admit a finite expansion with respect to some/any basis? The determination is to be made on the basis of a finite collection of discretely/noisily observed sample paths. We ...
ACADEMIC PRESS INC ELSEVIER SCIENCE2023Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective
Victor Panaretos, Neda Mohammadi Jouzdani
We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...
Amsterdam2023Inference and Computation for Sparsely Sampled Random Surfaces
Victor Panaretos, Tomas Rubin, Tomas Masák
Nonparametric inference for functional data over two-dimensional domains entails additional computational and statistical challenges, compared to the one-dimensional case. Separability of the covariance is commonly assumed to address these issues in the de ...
TAYLOR & FRANCIS INC2022Distribution-on-distribution regression via optimal transport maps
Victor Panaretos, Laya Ghodrati
We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...
OXFORD UNIV PRESS2022Random Surface Covariance Estimation by Shifted Partial Tracing
The problem of covariance estimation for replicated surface-valued processes is examined from the functional data analysis perspective. Considerations of statistical and computational efficiency often compel the use of separability of the covariance, even ...
TAYLOR & FRANCIS INC2022On the rate of convergence for the autocorrelation operator in functional autoregression
Victor Panaretos, Alessia Caponera
We consider the problem of estimating the autocorrelation operator of an autoregressive Hilbertian process. By means of a Tikhonov approach, we establish a general result that yields the convergence rate of the estimated autocorrelation operator as a funct ...
ELSEVIER2022CovNet: Covariance networks for functional data on multidimensional domains
Victor Panaretos, Soham Sarkar
Covariance estimation is ubiquitous in functional data analysis. Yet, the case of functional observations over multidimensional domains introduces computational and statistical challenges, rendering the standard methods effectively inapplicable. To address ...
WILEY2022