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Asymptotic expected sensitivity function and its applications to measures of monotone association
We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more...
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Stockout Reduction Using Forecasting Methods, the EOQ Model and a Safety Stock in a Peruvian SME in the Commercial Sector
Effective inventory management is a constant challenge for SMEs. Stockouts represent a significant obstacle that affects the operability and...
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The Influence Function of Scatter Halfspace Depth
In this work, we investigate robustness properties of scatter halfspace depth. Its influence function (IF) and sensitivity curve (SC) are studied in...
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Robust estimation of fixed effect parameters and variances of linear mixed models: the minimum density power divergence approach
Many real-life data sets can be analyzed using linear mixed models (LMMs). Since these are ordinarily based on normality assumptions, under small...
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An Application of Item Response Theory for Agricultural Sustainability Measurement
The concept of agricultural sustainability has been evolving since the mid-twentieth century. However, there is still not a universally accepted...
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Does Size Matter? Analysing the Financial Implications of COVID-19 on SMEs and Large Companies Using a Hybrid Methodology
Financial distress prediction holds significant value for stakeholders as it signals a company’s financial health. This study has three key....
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A Direct Approach in Extremal Index Estimation
The limit distribution of the normalized maxima of stationary sequences exists under specific conditions, even in the presence of some dependence...
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Robustness of Principal Component Analysis with Spearman’s Rank Matrix
This paper is concerned with robust principal component analysis (PCA) based on spatial sign and spatial rank vectors. The most common PC approach is...
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A refreshing take on the inverted Dirichlet via a mode parameterization with some statistical illustrations
The inverted Dirichlet (IDir) distribution is a popular choice for modeling multivariate data with positive support; however, its conventional...
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Can We Give the Maximum Sharpe Ratio Portfolio a Chance?
This chapter studies the applicability of the maximum Sharpe ratio (MaxSR) portfolio strategy in real-world settings. As shown by Okhrin and Schmidt...
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Questionnaire Design and Response Propensities for Labour Income Microdata
The income question in household surveys is one of the most socially sensitive constructs. Two problems that arise with social sensitivity concern...
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Optimal Band Selection Using Evolutionary Machine Learning to Improve the Accuracy of Hyper-spectral Images Classification: a Novel Migration-Based Particle Swarm Optimization
In the domain of real-world concept learning, feature selection plays a crucial role in accelerating learning processes and enhancing the quality of...
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Robust Estimation of General Linear Mixed Effects Models
The classical REML estimator for fitting a general linear mixed effects model is modified by bounding the terms appearing in the scoring equations....
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Diagnostic Trials
The term diagnostic trial is generally used in two different ways. A diagnostic trial type I describes studies that evaluate accuracy of diagnostic...
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Determinants of Non-Performing Loans: Evidence from Indian Banks
The incessant worsening in the asset quality of Indian banks is one of the prominent concerns for the regulator and policymakers, particularly in the...
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Design of Audit Programs
Audit programs—from a scientific perspective, natural experiments—are empirical studies in which the activities of firms, individuals, or groups are...
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Constrained Multivariate Functional Principal Components Analysis for Novel Outcomes in Eye-Tracking Experiments
Individuals with autism spectrum disorder (ASD) tend to experience greater difficulties with social communication and sensory information processing....
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Finding Outliers in Gaussian Model-based Clustering
Clustering, or unsupervised classification, is a task often plagued by outliers. Yet there is a paucity of work on handling outliers in clustering....
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A CNN-based multi-level face alignment approach for mitigating demographic bias in clinical populations
The investigation of demographic bias in facial analysis applications is a topic of growing interest with achievements in face recognition and gender...
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Data Analytics Incorporated with Machine Learning Approaches in Finance
From the last few decades, a huge volume of financial data has been generated from the various heterogeneous sources of financial institutions. This...