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Estimators of the multiple correlation coefficient: local robustness and confidence intervals. [PDF]
Statistical Papers, 2003 Many robust regression estimators are defined by minimizing a measure of spread of the residuals. An accompanying R-2-measure, or multiple correlation coefficient, is then easily obtained.
Croux, Christophe, Dehon, C
core +5 more sources
Globally robust confidence intervals for simple linear regression [PDF]
Computational Statistics & Data Analysis, 2010 It is well known that when the data may contain outliers or other departures from the assumed model, classical inference methods can be seriously affected and yield confidence levels much lower than the nominal ones. This paper proposes robust confidence intervals and tests for the parameters of the simple linear regression model that maintain their ...
J. Adrover, M. S. Barrera
semanticscholar +3 more sources
On Confidence Intervals of Robust Regression Estimators
Korean Journal of Applied Statistics, 2006 Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model.
Dong‐Hee Lee +2 more
openalex +4 more sources
Confidence Intervals Based on Robust Estimators
Journal of Modern Applied Statistical Methods, 2008 Meral ÇETİN, Serpil Aktaş
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Is Seeing Believing? A Practitioner’s Perspective on High-Dimensional Statistical Inference in Cancer Genomics Studies [PDF]
EntropyVariable selection methods have been extensively developed for and applied to cancer genomics data to identify important omics features associated with complex disease traits, including cancer outcomes. However, the reliability and reproducibility of the
Kun Fan +5 more
doaj +2 more sources
Inference for Median and a Generalization of HulC [PDF]
arXivConstructing distribution-free confidence intervals for the median, a classic problem in statistics, has seen numerous solutions in the literature. While coverage validity has received ample attention, less has been explored about interval width. Our study breaks new ground by investigating the width of these intervals under non-standard assumptions ...
Kuchibhotla, Arun Kumar, Paul, Manit
arxiv +2 more sources
CESER: An R Package to Compute Cluster Estimated Standard Errors
Journal of Open Research Software, 2021 This paper presents an implementation in R of the Cluster Estimated Standard Errors (CESE) proposed by [12]. The method estimates the covariance matrix of the estimated coefficients of linear models in grouped data sets with correlation among ...
Diogo Ferrari
doaj +1 more source
Confidence interval methods for antimicrobial resistance surveillance data
Antimicrobial Resistance and Infection Control, 2021 Background Antimicrobial resistance (AMR) is one of the greatest global health challenges today, but burden assessment is hindered by uncertainty of AMR prevalence estimates.
Erta Kalanxhi +3 more
doaj +1 more source
Sensors, 2021 This paper analyzes 12 years of tropospheric ozone (O3) concentration measurements using robust techniques. The measurements were taken at an air quality monitoring station called Belisario, which is in Quito, Ecuador; the data collection time period was
Wilmar Hernandez +4 more
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