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A Biclustering Approach via Mixture of Latent Trait Analyzers for the Analysis of Digital Divide in Italy
We employ an extension of the Mixture of Latent Trait Analyzers (MLTA) model to analyse the digital divide in Italy in a biclustering perspective. In...
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A Comparison of Extreme Gradient and Gaussian Process Boosting for a Spatial Logistic Regression on Satellite Data
A popular and successful method of obtaining regression models using decision tree learners is XGBoost. However, the method implicitly assumes...
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Spatial Confounding in Gradient Boosting
Collinearity between covariates and spatial effects can lead to a bias in the corresponding fixed effects’ estimates known as spatial confounding....
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Sparse Intrinsic Gaussian Processes for Prediction on Manifolds: Extending Applications to Environmental Contexts
Traditional Gaussian Processes are limited in their application by complex boundaries and intricately structured manifolds, such as when predicting...
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A Distance-Based Statistic for Goodness-of-Fit Assessment
The modelling of count data in real world scenarios often requires models that address over-dispersion. Within the generalized linear modeling...
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Wilcoxon Rank Sum Scan Statistics for Continuous Data with Outliers
In this chapter, we investigate the performance of several Wilcoxon rank sum scan statistics in detecting a local change in population mean, in the...
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The Most Important Knowledge by 27 Revolutionary Findings and the Outlook of This Book
The author completed a new discriminant theory (Theory1) that solved four discriminant problems by RIP (Revised Optimal LDF) and two Facts in 2015....
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Test Pass/Fail Judgment and Japanese Compact Cars and Regular Cars
I introduce two self-evident LSDs. The pass/fail judgments of exams are self-evident LSD. Suppose two scores, T1 and T2, and 50 points is the passing...
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First Theory of Cancer Gene Data Analysis by 169 Microarrays—Four Universal Data Structures of Discriminant Data
The new discriminant theory (Theory1) analyzed six microarrays having two classes. The Revised IP Optimal LDF (RIP) finds the minimum number of...
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The Spatial Structure of Housing Prices in Madrid: Evidence from Spatio-temporal Scan Statistics
We apply spatio-temporal scan statistics on the distributions of asking price per meter squared for various segments of the housing market (attics,...
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The Scan Statistic for Multidimensional Data and Social Media Applications
This chapter reviews the literature on the scan statistic with particular emphasis on its application. The chapter considers the application of the...
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Run and Scan Rules in Statistical Process Monitoring
In this paper, we provide an overview of the use of run and scan rules in statistical process monitoring. Although we focus on control charts,...
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On the Exact Distributions of Pattern Statistics for a Sequence of Binary Trials: A Combinatorial Approach
Consider a sequence of exchangeable or Markov-dependent binary (zero-one) trials. A sequence of independent and identically distributed binary trials...
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ScanZID: Spatial Scan Statistics with Zero Inflation and Dispersion
The spatial scan statistic is one of the most important methods to detect and monitor spatial disease clusters. Usually it is assumed that disease...
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Shocks, Scans, and Reliability Systems
This chapter summarizes the close connection between one of the widely studied shock models known as δ-shock model and runs/scans. Under discrete...
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Variable Window Scan Statistics: Alternatives to Generalized Likelihood Ratio Tests
Classical variable window scan statistics are based on likelihood ratios issued from parametric models. However, these likelihood ratios do not give...
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Wilcoxon Rank Sum Scan Statistics for Continuous Data with Outliers
In this chapter, we investigate the performance of several Wilcoxon rank sum scan statistics in detecting a local change in population mean, in the...
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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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Discrete Scan Statistics for Higher-Order Markovian Sequences
In this chapter we review methods for computing probabilities of the discrete scan statistic. Most of the presented results are for independent...
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Discrete Scan Statistics Generated by Dependent Trials and Their Applications in Reliability
The chapter is concerned with discrete scan statistic based on a sequence of dependent binary trials. In particular, the existing results are...