Robust linear model selection based on least angle regression
JA Khan, S Van Aelst, RH Zamar - Journal of the American …, 2007 - Taylor & Francis
In this article we consider the problem of building a linear prediction model when the
number of candidate predictors is large and the data possibly contain anomalies that are …
number of candidate predictors is large and the data possibly contain anomalies that are …
[HTML][HTML] FSDA: A MATLAB toolbox for robust analysis and interactive data exploration
M Riani, D Perrotta, F Torti - Chemometrics and Intelligent Laboratory …, 2012 - Elsevier
We present the FSDA (Forward Search for Data Analysis) toolbox, a new software library
that extends MATLAB and its Statistics Toolbox to support a robust and efficient analysis of …
that extends MATLAB and its Statistics Toolbox to support a robust and efficient analysis of …
Monitoring robust regression
Monitoring robust regression Page 1 Electronic Journal of Statistics Vol. 8 (2014) 646–677
ISSN: 1935-7524 DOI: 10.1214/14-EJS897 Monitoring robust regression Marco Riani, Andrea …
ISSN: 1935-7524 DOI: 10.1214/14-EJS897 Monitoring robust regression Marco Riani, Andrea …
Least median of squares filtering of locally optimal point matches for compressible flow image registration
E Castillo, R Castillo, B White, J Rojo… - Physics in Medicine & …, 2012 - iopscience.iop.org
Compressible flow based image registration operates under the assumption that the mass of
the imaged material is conserved from one image to the next. Depending on how the mass …
the imaged material is conserved from one image to the next. Depending on how the mass …
[HTML][HTML] Strong consistency and robustness of the forward search estimator of multivariate location and scatter
Abstract The Forward Search is a powerful general method for detecting anomalies in
structured data, whose diagnostic power has been shown in many statistical contexts …
structured data, whose diagnostic power has been shown in many statistical contexts …
[图书][B] Evolutionary statistical procedures: an evolutionary computation approach to statistical procedures designs and applications
R Baragona, F Battaglia, I Poli - 2011 - books.google.com
This proposed text appears to be a good introduction to evolutionary computation for use in
applied statistics research. The authors draw from a vast base of knowledge about the …
applied statistics research. The authors draw from a vast base of knowledge about the …
Quadratic penalty method for intensity‐based deformable image registration and 4DCT lung motion recovery
E Castillo - Medical physics, 2019 - Wiley Online Library
Intensity‐based deformable image registration (DIR) requires minimizing an image
dissimilarity metric. Imaged anatomy, such as bones and vasculature, as well as the …
dissimilarity metric. Imaged anatomy, such as bones and vasculature, as well as the …
The analysis of transformations for profit-and-loss data
We analyse data on the performance of investment funds, 99 out of 309 of which report a
loss, and on the profitability of 1405 firms, 407 of which report losses. The problem in both …
loss, and on the profitability of 1405 firms, 407 of which report losses. The problem in both …
Testing normality in the presence of outliers
D Coin - Statistical Methods and Applications, 2008 - Springer
Statistical models are often based on normal distributions and procedures for testing this
distributional assumption are needed. Many goodness-of-fit tests suffer from the presence of …
distributional assumption are needed. Many goodness-of-fit tests suffer from the presence of …
[HTML][HTML] A diagnostic method for simultaneous feature selection and outlier identification in linear regression
RS Menjoge, RE Welsch - Computational Statistics & Data Analysis, 2010 - Elsevier
A diagnostic method along the lines of forward search is proposed to simultaneously study
the effect of individual observations and features on the inferences made in linear …
the effect of individual observations and features on the inferences made in linear …