3 citations · 6 across the 10 of their papers we have counts for
14 papers
Inference for Fréchet Regression
Wookyeong Song, Paromita Dubey, Hans-Georg Müller +1
Linear regression is widely used to model relationships between responses and predictors. In modern applications, one encounters data where the responses are non-Euclidean random o…
LLmFPCA-detect: LLM-powered Multivariate Functional PCA for Anomaly Detection in Sparse Longitudinal Texts
Prasanjit Dubey, Aritra Guha, Zhengyi Zhou +3
Sparse longitudinal (SL) textual data arises when individuals generate text repeatedly over time (e.g., customer reviews, occasional social media posts, electronic medical records…
DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
Kyum Kim, Yaqing Chen, Paromita Dubey
Regression with non-Euclidean responses---e.g., probability distributions, networks, symmetric positive-definite matrices, and compositions---has become increasingly important in m…
Iterative Exploration-Driven Sparse SDP Clustering via Thompson Sampling
Jongmin Mun, Paromita Dubey, Yingying Fan
High-dimensional sparse clustering is a challenging combinatorial problem due to the tight coupling between cluster assignment and variable selection. We demonstrate that semidefin…
DiPMInd: Distance Profile based Mutual Independence testing for random objects
Yaqing Chen, Paromita Dubey
This paper develops a novel unified framework for testing mutual independence among random objects residing in possibly different metric spaces. The framework generalizes existing…
Change Point Inference for Non-Euclidean Data Sequences using Distance Profiles
Paromita Dubey, Minxing Zheng
We introduce a powerful scan statistic and the corresponding test for detecting the presence and pinpointing the location of a change point within the distribution of a data sequen…
Metric Statistics: Exploration and Inference for Random Objects With Distance Profiles
Paromita Dubey, Yaqing Chen, Hans-Georg Müller
This article provides an overview on the statistical modeling of complex data as increasingly encountered in modern data analysis. It is argued that such data can often be describe…
Online network change point detection with missing values and temporal dependence
Haotian Xu, Paromita Dubey, Yi Yu
In this paper we study online change point detection in dynamic networks with time heterogeneous missing pattern within networks and dependence across the time course. The missingn…
Learning delay dynamics for multivariate stochastic processes, with application to the prediction of the growth rate of COVID-19 cases in the United States
Paromita Dubey, Yaqing Chen, Álvaro Gajardo +5
Delay differential equations form the underpinning of many complex dynamical systems. The forward problem of solving random differential equations with delay has received increasin…
Modeling Time-Varying Random Objects and Dynamic Networks
Paromita Dubey, Hans-Georg Müller
Samples of dynamic or time-varying networks and other random object data such as time-varying probability distributions are increasingly encountered in modern data analysis. Common…
Fréchet Change Point Detection
Paromita Dubey, Hans-Georg Müller
We propose a method to infer the presence and location of change-points in the distribution of a sequence of independent data taking values in a general metric space, where change-…
Functional Models for Time-Varying Random Objects
Paromita Dubey, Hans-Georg Müller
In recent years, samples of time-varying object data such as time-varying networks that are not in a vector space have been increasingly collected. These data can be viewed as elem…
Fréchet Analysis Of Variance For Random Objects
Paromita Dubey, Hans-Georg Müller
Fréchet mean and variance provide a way of obtaining mean and variance for general metric space valued random variables and can be used for statistical analysis of data objects tha…
Modeling Bimodal Discrete Data Using Conway-Maxwell-Poisson Mixture Models
Pragya Sur, Galit Shmueli, Smarajit Bose +1
Bimodal truncated count distributions are frequently observed in aggregate survey data and in user ratings when respondents are mixed in their opinion. They also arise in censored…