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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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Multivariate understanding of income and expenditure in United States households with statistical learning
In recent decades, data-driven approaches have been developed to analyze demographic and economic surveys on a large scale. Despite advances in...
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The Upcrossing Rate via the Characteristic Function
As was detailed in Chap. 4, a key function for a practical assessment of the extreme value distribution of stochastic response processes is the...
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Band depth based initialization of K-means for functional data clustering
The k -Means algorithm is one of the most popular choices for clustering data but is well-known to be sensitive to the initialization process. There...
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Using sequential statistical tests for efficient hyperparameter tuning
Hyperparameter tuning is one of the most time-consuming parts in machine learning. Despite the existence of modern optimization algorithms that...
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Model Oriented Statistical Analysis for Cancer Problems
The target of this paper is to refer on model oriented data analysis for cancer problem. There is a solid background on statistical modelling and we...
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Robust Depth-Based Inference in Elliptical Models
Elliptical models are the most important family of multivariate probability distributions. We explore the properties of these distributions with...
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Review of Statistical Approaches for Modeling High-Frequency Trading Data
Due to technological advancements over the last two decades, algorithmic trading strategies are now widely used in financial markets. In turn, these...
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A variable selection procedure for depth measures
We herein introduce variable selection procedures based on depth similarity, aimed at identifying a small subset of variables that can better explain...
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A Statistical Boost to Assess Water Quality
Water quality in coastal and oceanic zones promotes various benefits for the regional economy, socio-cultural values, and biodiversity. Chlorophyll-a...
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Statistical Decisions
Data are often collected and analysed to answer a particular question. For instance, when modifying an existing product, one wants to know whether...
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Simultaneous monitoring of origin and scale in left-bounded processes via depth
A novel notion of depth for the origin and scale of a distribution with left-bounded support, like those modelling lifetime data, is presented. This...
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Statistical Tables
Statistical tables supplement scientific data visualization for the analysis of categorical data. This type of data is exemplified by, but not...
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Depth in Infinite-dimensional Spaces
Depth is a statistical tool that aims to introduce sensible data-dependent ordering of points in multivariate / function spaces. In theory, this...
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Parametric Statistical Models
Now that we have introduced probability models, we have the tools we need to put our statisticians’ hats on. We want to make a probabilistic model...
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Statistical Challenges in Mutational Signature Analyses of Cancer Sequencing Data
Cancer is a disease driven and characterised by mutations in the DNA. Different categorisations of DNA mutations have allowed the identification of...
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Two Statistical Degradation Models of Batteries Under Different Operating Conditions
The commercialization of electric vehicles (EVs) demands higher performances of rechargeable batteries. Accurate assessments of state of health (SOH)...
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A notion of depth for sparse functional data
Data depth is a well-known and useful nonparametric tool for analyzing functional data. It provides a novel way of ranking a sample of curves from...
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A Statistical Perspective on the Challenges in Molecular Microbial Biology
High throughput sequencing (HTS)-based technology enables identifying and quantifying non-culturable microbial organisms in all environments....
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Directional Supervised Learning Through Depth Functions: An Application to ECG Waves Analysis
The present work investigates arrhythmias which can be detected from Electrocardiography (ECG) waves. Detecting cardiac arrhythmia helps indeed to...