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Partial linear regression of compositional data
We study a partial linear model in which the response is compositional and the predictors include both compositional and Euclidean variables. We...
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Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection
Many existing procedures for detecting multiple change-points in data sequences fail in frequent-change-point scenarios. This article proposes a new...
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Generating Function Methods for Run and Scan Statistics
Runs and pattern statistics have found successful applications in various fields. Many classical results of distributions of runs were obtained by...
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Data Center Organization and Optimization Strategy as a K-Ary N-Cube Topology
Data center deployments are increasing because of the ongoing expansion of IoT environments, which require data centers of a small to medium size,...
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Measures of Association
This chapter starts with a discussion on the historical development of correlation coefficients. It then discusses the population and sample...
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Health Monitoring Techniques Using Scan Statistics
Scan statistics appeared in the statistics literature about half a century ago, and since then many papers suggesting either extensions and...
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Scan Statistics Applications in Genomics
The area of scan statistics encompasses a broad class of methods for detecting clusters of events. These methods have been applied to identify...
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Detecting multiple generalized change-points by isolating single ones
We introduce a new approach, called Isolate-Detect (ID), for the consistent estimation of the number and location of multiple generalized...
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Ranks, copulas, and permutons
We review a recent development at the interface between discrete mathematics on one hand and probability theory and statistics on the other,...
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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...
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Some Notes on Types of Symmetry for Crossover Designs
Crossover designs are used to assign multiple treatments to the same unit over a period of time. In the search of optimal crossover designs,...
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Bayesian Multiple Change-Points Detection in a Normal Model with Heterogeneous Variances
This study considers the problem of multiple change-points detection. For this problem, we develop an objective Bayesian multiple change-points...
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Prediction Modeling
Predictive modeling can be defined as modeling the historical data using statistical and machine learning techniques to predict future observations....
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Joint Reliability of Two Consecutive-(1, l) or (2, k)-out-of-(2, n): F Type Systems and Its Application in Smart Street Light Deployment
To investigate some complex practical systems, such as a smart street light system composed of symmetrically deployed lighting and sensing equipment...
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Relaxing Monotonicity in Endogenous Selection Models and Application to Surveys
This paper considers endogenous selection models, in particular, nonparametric ones. Estimating the unconditional law of the outcomes is possible...
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Two Simple but Efficient Algorithms to Recognize Robinson Dissimilarities
A dissimilarity d on a set S of size n is said to be Robinson if its matrix can be symmetrically permuted so that its elements do not decrease when...
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A Note on Circular m-consecutive-k-out-of-n:F Systems
In this chapter, more generalized version of m-consecutive-k-out-of-n:F system is introduced in circular case, that is named as circular...
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Two-stage data segmentation permitting multiscale change points, heavy tails and dependence
The segmentation of a time series into piecewise stationary segments is an important problem both in time series analysis and signal processing. In...
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On Homogeneous Multivariate Distributions in Random Occupancy Models and Their Applications
In this article, we consider random occupancy models and the related problems based on the methods of generating functions. The waiting time...
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Second-order and local characteristics of network intensity functions
The last decade has witnessed an increase of interest in the spatial analysis of structured point patterns over networks whose analysis is...
