Search
Search Results
-
A sequential feature selection approach to change point detection in mean-shift change point models
Change point detection is an important area of scientific research and has applications in a wide range of fields. In this paper, we propose a...
-
Gradual change-point analysis based on Spearman matrices for multivariate time series
It may happen that the behavior of a multivariate time series is such that the underlying joint distribution is gradually moving from one...
-
Change point detection in text data
The analysis of text data using artificial intelligence and statistical methods has become increasingly important in recent years. One application is...
-
Bayesian Robustness in Change Point Analysis
This paper focuses on robustness analysis of non-exchangeable product partition models (PPM), which are widely used to detect multiple change points....
-
Adaptive parametric change point inference under covariance structure changes
The article offers a method for estimating the volatility covariance matrix of vectors of financial time series data using a change point approach....
-
Exact distribution of change-point MLE for a Multivariate normal sequence
This paper presents the derivation of an expression for computing the exact distribution of the change-point maximum likelihood estimate (MLE) in the...
-
Multipartition model for multiple change point identification
The product partition model (PPM) is widely used for detecting multiple change points. Because changes in different parameters may occur at different...
-
Change-point detection in a tensor regression model
In this paper, we consider an inference problem in a tensor regression model with one change-point. Specifically, we consider a general hypothesis...
-
Change point in variance of fractionally integrated noise
This paper studies the quasi-maximum likelihood estimator (quasi-MLE) of a change point in variance for the fractionally integrated noise with memory...
-
Multiple change point detection for high-dimensional data
This research investigates the detection of multiple change points in high-dimensional data without particular sparse or dense structure, where the...
-
On Robust Change Point Detection and Estimation in Multisubject Studies
A variety of change point estimation and detection algorithms have been developed for random variables observed over time. The acquisition of data in...
-
Change point detection in high dimensional data with U-statistics
We consider the problem of detecting distributional changes in a sequence of high dimensional data. Our approach combines two separate statistics...
-
Change Point Detection in Length-Biased Weibull Distribution for Random Censored Data Based on Modified Information Criterion
In this article, we study the change point problem of length-biased Weibull distribution under the scenario of random censorship. We construct the...
-
A weighted U-statistic based change point test for multivariate time series
In this paper we study the change point detection for the mean of multivariate time series. We construct the weighted U-statistic change point tests...
-
Change Point Detection in Linear Failure Rate Distribution Under Random Censorship
In this paper, we develop a procedure for change point detection problem in the linear failure rate (LFR) distribution for random censored data. The...
-
Z-Process Method for Change Point Problems in Time Series
Z-process method was introduced as a general unified approach based on partial estimation functions to construct a statistical test in change point...
-
Robust change-point detection for functional time series based on U-statistics and dependent wild bootstrap
The aim of this paper is to develop a change-point test for functional time series that uses the full functional information and is less sensitive to...
-
3D Point Cloud Semantic Segmentation Through Functional Data Analysis
Here, we propose a method for the semantic segmentation of 3D point clouds based on functional data analysis. For each point of a training set, a...
-
Genetic algorithm with a Bayesian approach for multiple change-point detection in time series of counting exceedances for specific thresholds
Although the applications of Non-Homogeneous Poisson Processes (NHPP) to model and study the threshold overshoots of interest in different time...
-
A computationally efficient and flexible algorithm for high dimensional mean and covariance matrix change point models
This paper proposes a computationally efficient algorithm, FBS (Fast Binary Segmentation), for both single and multiple change point detection under...
