Statistics (Scholarly Publications)
Recent Submissions
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Learning Mixtures of Gaussian Processes through Random Projection
(2024)We propose an ensemble clustering framework to uncover latent cluster labels in functional data generated from a Gaussian process mixture. Our method exploits the fact that the projection coefficients of the functional ... -
A Theoretical Analysis of Density Peaks Clustering and the Component-wise Peak-Finding Algorithm
(2024)Density peaks clustering detects modes as points with high density and large distance to points of higher density. Each non-mode point is assigned to the same cluster as its nearest neighbor of higher density. Density ... -
Reinforced EM Algorithm for Clustering with Gaussian Mixture Models
(2023)Methods that employ the EM algorithm for parameter estimation typically face the notorious yet unsolved problem that the initialization input significantly impacts the algorithm output. We here develop a Reinforced ... -
Incorporating Ignorance within Game Theory: An Imprecise Probability Approach
(2023)Ignorance within non-cooperative games, reflected as a player’s uncertain prefer- ences towards a game’s outcome, is examined from a Bayesian point of view. This topic has had scarce treatment in the literature, which ... -
Saddlepoint Approximation for the Generalized Inverse Gaussian Levy Process
(2022)The generalized inverse Gaussian (GIG) Lévy process is a limit of compound Poisson processes, including the stationary gamma process and the stationary inverse Gaussian process as special cases. However, fitting the GIG ... -
DCF: An Efficient and Robust Density-Based Clustering Method
(2021)Density-based clustering methods have been shown to achieve promising results in modern data mining applications. A recent approach, Density Peaks Clustering (DPC), detects modes as points with high density and large ... -
Semantic image segmentation based on spatial relationships and inexact graph matching
(2020)We propose a method for semantic image segmentation, combining a deep neural network and spatial relationships between image regions, encoded in a graph representation of the scene. Our proposal is based on inexact graph ... -
A Heuristic Policy for Maintaining Multiple Multi-State Systems
(2020)This work is concerned with the optimal allocation of limited maintenance resources among a collection of competing multi-state systems, and the dynamic of each multi-state system is modelled by a Markov chain. Determining ... -
A Bayesian approach to modeling mortgage default and prepayment
(2019)In this paper we present a Bayesian competing risk proportional hazards model to describe mortgage defaults and prepayments. We develop Bayesian inference for the model using Markov chain Monte Carlo methods. Implementation ... -
Estimating redshift distributions using Hierarchical Logistic Gaussian processes
(2019)This work uses hierarchical logistic Gaussian processes to infer true redshift distributions of samples of galaxies, through their cross-correlations with spatially overlapping spectroscopic samples. We demonstrate that ... -
Vine Copula Approximation: A Generic Method for Coping with Conditional Dependence
(2018)Pair-copula constructions (or vine copulas) are structured, in the layout of vines, with bivariate copulas and conditional bivariate copulas. The main contribution of the current work is an approach to the long-standing ... -
Model selection with application to gamma process and inverse Gaussian process
(2016)The gamma process and the inverse Gaussian process are widely used in condition-based maintenance. Both are suitable for modelling monotonically increasing degradation processes. Hence, one challenge for practitioners ... -
Degradation-Based Maintenance Using Stochastic Filtering for Systems under Imperfect Maintenance
(2015)The stationaryWiener process is widely used in modeling degradation processes, mainly due to the existence of an analytical expression of the first hitting time distribution. However, it is only appropriate for modelling ... -
A Stochastic EM Algorithm for Progressively Censored Data Analysis
(2014)Progressive censoring technique is useful in lifetime data analysis. Simple approaches to progressive data analysis are crucial for its widespread adoption by reliability engineers. This study develops an efficient yet ... -
A Condition-Based Maintenance Strategy for Heterogeneous Populations
(2014)This paper develops a maintenance strategy, called inspection-replacement policy, to cope with heterogeneous populations. Burn-in is the procedure by which most of the defective products in a heterogeneous population can ... -
Lower Confidence Limit for Reliability Based on Grouped Data with a Quantile Filling Algorithm
(2014)The purpose of this article is to derive a lower confidence limit for reliability given a grouped data set. This is done by using a quantile filling algorithm which generates pseudo failure data from grouped data. A general ... -
A Bivariate Maintenance Policy for Multi-State Repairable Systems with Monotone Process
(2013)In this paper, a sequential failure limit maintenance policy for a repairable system is studied. The system is assumed to have states, including one working state and failure states, and the multiple failure states are ... -
Continuous-Observation Partially Observable Semi-Markov Decision Processes for Machine Maintenance
(2017)Partially observable semi-Markov decision processes (POSMDPs) provide a rich framework for planning under both state transition uncertainty and observation uncertainty. In this paper, we widen the literature on POSMDP by ... -
An Ameliorated Improvement Factor Model for Imperfect Maintenance and Its Goodness of Fit
(2017)Maintenance actions can be classified, according to their efficiency, into three categories: perfect maintenance, imperfect maintenance, and minimal maintenance. To date, the literature on imperfect maintenance is voluminous, ...