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Tests for a Structural Break for Nonnegative Integer-Valued Time Series
We investigate tests for a structural break for nonnegative integer-valued time series. This topic has been intensively studied in recent years. We...
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A general panel break test based on the self-normalization method
We propose new break tests for parameters such as mean, variance, quantile and others of panel data sets, in a general setup based on the...
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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...
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ROBOUT: a conditional outlier detection methodology for high-dimensional data
This paper presents a methodology, called ROBOUT, to identify outliers conditional on a high-dimensional noisy information set. In particular, ROBOUT...
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A general procedure for change-point detection in multivariate time series
We consider the change-point detection in a general class of time series models, including multivariate continuous and integer- valued time series....
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Empirical likelihood change point detection in quantile regression models
Quantile regression is an extension of linear regression which estimates a conditional quantile of interest. In this paper, we propose an empirical...
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Detection of multiple change-points in high-dimensional panel data with cross-sectional and temporal dependence
We consider the detection of multiple change-points in a high-dimensional time series exhibiting both cross-sectional and temporal dependence....
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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...
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Text-Based Causal Inference on Irony and Sarcasm Detection
The state-of-the-art NLP models’ success advanced significantly as their complexity increased in recent years. However, these models tend to consider...
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An Improved Forecasting and Detection of Structural Breaks in Time Series Using Fuzzy Techniques
In this paper, we address nonstatistical methods for forecasting and detection of structural breaks in time series. Our methods are based on the...
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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...
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Poisson QMLE for change-point detection in general integer-valued time series models
We consider together the retrospective and the sequential change-point detection in a general class of integer-valued time series. The conditional...
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Block bootstrap** for a panel mean break test
We consider block bootstrap**s for panel mean change test of the squared CUSUM test of Horváth and Hušková (J Time Ser Anal 33:631–648, 2012): the...
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Most recent changepoint detection in censored panel data
This study aims to detect the most recent changepoint in censored panel data by ignoring dependence within and between segments as well as taking...
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A Bayesian piecewise linear model for the detection of breakpoints in housing prices
Statistical thresholds occur when the changes in the relationships between a response and predictor variables are not linear but abrupt at some...
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Scale Invariant and Robust Pattern Identification in Univariate Time Series, with Application to Growth Trend Detection in Music Streaming Data
A method is proposed to identify a pre-defined pattern in univariate time series. The pattern could describe an expected trend, for example, the...
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Outlier detection in non-elliptical data by kernel MRCD
The minimum regularized covariance determinant method (MRCD) is a robust estimator for multivariate location and scatter, which detects outliers by...
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High-dimensional changepoint detection via a geometrically inspired map**
High-dimensional changepoint analysis is a growing area of research and has applications in a wide range of fields. The aim is to accurately and...
