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A survey of robust statistics [PDF]

, 2018
We argue that robust statistics has multiple goals, which are not always aligned. Robust thinking grew out of data analysis and the realisation that empirical evidence is at times supported merely by one or a few observations.
Morgenthaler, Stephan
core   +1 more source

Tax Audit in Turkiye: Simulation and Estimations Based on Kernel and Weight Functions

Chaos Theory and Applications
This research examines the use of kernel estimation and $FindDistribution$ methods in $Mathematica$ software to analyze the ratio of taxpayer audits to total taxpayers, focusing on two large populations: one with approximately 80,000 audits per 100,000 ...
Mehmet Niyazi Çankaya, Murat Aydın
doaj   +1 more source

Resilient Distributed Optimization Algorithms for Resource Allocation [PDF]

, 2019
Distributed algorithms provide flexibility over centralized algorithms for resource allocation problems, e.g., cyber-physical systems. However, the distributed nature of these algorithms often makes the systems susceptible to man-in-the-middle attacks ...
Alizadeh, Mahnoosh, Uribe, Cesar, Wai, Hoi-To   +2 more
core   +1 more source

Resistant Nonparametric Smoothing with S-PLUS [PDF]

In this paper we introduce and illustrate the use of an S-PLUS set of functions to fit M-type smoothing splines with the smoothing parameter chosen by a robust criterion (either a robust version of cross-validation or a robust version of Mallows's Cp ...
Eva Cantoni
core   +1 more source

Robust Econometrics [PDF]

Econometrics often deals with data under, from the statistical point of view, non-standard conditions such as heteroscedasticity or measurement errors and the estimation methods need thus be either adopted to such conditions or be at least insensitive to
Pavel Cizek, Wolfgang Härdle
core  

Designing cancer immunotherapy trials with delayed treatment effect using maximin efficiency robust statistics. [PDF]

Pharm Stat, 2020
Ding X, Wu J.
europepmc   +1 more source

Robust Nonparametric Early Stopping in Tree Ensembles via IQR-Scale Change-Point Detection

Mathematics
Tree ensembles—Random Forests (RFs) and Gradient Boosting Machines (GBMs)—often stabilize before all trees are evaluated. We study early stopping as a nonparametric change-point problem on prediction increments.
Sooyoung Jang, Changbeom Choi
doaj   +1 more source

Portfolio Decisions with Higher Order Moments [PDF]

In this paper, we address the global optimization of two interesting nonconvex problems in finance. We relax the normality assumption underlying the classical Markowitz mean-variance portfolio optimization model and consider the incorporation of skewness
Berc Rustem, P. M. Kleniati
core  

A Nonlinear Entropic Variational Model for Image Filtering

EURASIP Journal on Advances in Signal Processing, 2004
We propose an information-theoretic variational filter for image denoising. It is a result of minimizing a functional subject to some noise constraints, and takes a hybrid form of a negentropy variational integral for small gradient magnitudes and a ...
Krim Hamid, Zerubia Josiane, Ben Hamza A
doaj   +1 more source

RFreak-An R-package for evolutionary computation [PDF]

RFreak is an R package providing a framework for evolutionary computation. By enwrapping the functionality of an evolutionary algorithm kit written in Java, it offers an easy way to do evolutionary computation in R.
Nunkesser, Robin
core