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Regression Analysis of Stochastic Fatigue Crack Growth Model in a Martingale Difference Framework
In the present paper, we are mainly concerned with the degradation mechanism that arises in fatigue crack growth (FCG). The crack evolution mechanism...
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De-identifying Clinical Trial Data
Conducting clinical trials involves collecting detailed health information about participants. Privacy of individual participants is important and...
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Prison IOT
The Internet of Things in prison refers to technology installed in the prison, such as the RFID radio frequency identification of objects that is...
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Potential to Density via Poisson Equation: Application to Bespoke Learning of Gravitational Mass Density in Real Galaxy
In multiple real-world dynamical systems, structural properties can be deterministically linked to the evolution-driving function. For example, in...
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A modeler’s guide to extreme value software
This review paper surveys recent development in software implementations for extreme value analyses since the publication of Stephenson and Gilleland...
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Questions that Can Be Answered with CFA
Configural frequency analysis (CFA) is unconventional in that it, unlike most other categorical methods of inferential statistics, aims at...
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Modeling Long Term Return Distribution and Nonparametric Market Risk Estimation
The log-return of an asset is the change in the asset price, measured in natural logarithmic scale, over a certain time period. We introduce a...
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Simple powerful robust tests based on sign depth
Up to now, powerful outlier robust tests for linear models are based on M-estimators and are quite complicated. On the other hand, the simple robust...
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Semi-functional partially linear regression model with responses missing at random
This paper focuses on semi-functional partially linear regression model, where a scalar response variable with missing at random is explained by a...
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Uniform in Bandwidth Consistency of Conditional U-statistics Adaptive to Intrinsic Dimension in Presence of Censored Data
U -statistics represent a fundamental class of statistics from modelling quantities of interest defined by multi-subject responses. U -statistics...
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Experimental Data Analysis
The technical and more extensive part of this chapter describes how to apply statistical and probabilistic methods to the various types of...
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Stochastic Volatility Models Predictive Relevance for Equity Markets
This paper builds and implements multifactor stochastic volatility models where the main objective is step ahead volatility prediction and to...
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Analysis of stochastic gradient descent in continuous time
Stochastic gradient descent is an optimisation method that combines classical gradient descent with random subsampling within the target functional....
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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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Non-asymptotic analysis and inference for an outlyingness induced winsorized mean
Robust estimation of a mean vector, a topic regarded as obsolete in the traditional robust statistics community, has recently surged in machine...
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Statistical Inference and Bootstrap**
In this chapter we introduce basic concepts and methods of statistical inference. The focus is on estimating the parameters of statistical...
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The Bahadur Representation for Empirical and Smooth Quantile Estimators Under Association
In this paper, the Bahadur representation of the empirical and Bernstein polynomials estimators of the quantile function based on associated...
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Tail Maximal Dependence in Bivariate Models: Estimation and Applications
AbstractAssessing dependence within co-movements of financial instruments has been of much interest in risk management. Typically, indices of tail...
