3 citations · 6 across the 10 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…