Symmetrically Trimmed Least Squares Estimation for Tobit Models [PDF]
Econometrica, 1986 This paper proposes alternatives to maximum likelihood estimation of the censored and truncated regression models (known to economists as ``Tobit'' models). The proposed estimators are based upon symmetric censoring or truncation of the upper tail of the distribution of the dependent variable.
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A Monte Carlo Comparison of Regression Estimators When the Error Distribution is Long-Tailed Symmetric [PDF]
, 2009 The performances of the ordinary least squares (OLS), modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares (WIN), trimmed least squares (TLS), Theil’s (Theil) and weighted Theil’s (Weighted Theil) estimators are ...
Mutan, Oya Can, Şenoğlu, Birdal
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truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models
Journal of Statistical Software, 2014 Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use ...
Maria Karlsson, Anita Lindmark
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Enhanced Dynamic Performance in Hybrid Power System Using a Designed ALTS-PFPNN Controller
Energies, 2022 The large-scale, nonlinear and uncertain factors of hybrid power systems (HPS) have always been difficult problems in dynamic stability control. This research mainly focuses on the dynamic and transient stability performance of large HPS under various ...
Kai-Hung Lu +2 more
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RobPer: An R Package to Calculate Periodograms for Light Curves Based on Robust Regression
Journal of Statistical Software, 2016 An important task in astroparticle physics is the detection of periodicities in irregularly sampled time series, called light curves. The classic Fourier periodogram cannot deal with irregular sampling and with the measurement accuracies that are ...
Anita M. Thieler +2 more
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Approximate least trimmed sum of squares fitting and applications in image analysis [PDF]
, 2013 The least trimmed sum of squares (LTS) regression estimation criterion is a robust statistical method for model fitting in the presence of outliers. Compared with the classical least squares estimator, which uses the entire data set for regression and is
Shen, C. +3 more
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Combining some Biased Estimation Methods with Least Trimmed Squares Regression and its Application
Revista Colombiana de EstadísticaIn the case of multicollinearity and outliers in regression analysis, the researchers are encouraged to deal with two problems simultaneously. Biased methods based on robust estimators are useful for estimating the regression coefficients for such cases.
BETÜL KAN-KILINÇ, OZLEM ALPU
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Linear Regression for Heavy Tails
Risks, 2018 There exist several estimators of the regression line in the simple linear regression: Least Squares, Least Absolute Deviation, Right Median, Theil–Sen, Weighted Balance, and Least Trimmed Squares.
Guus Balkema, Paul Embrechts
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MUREN: a robust and multi-reference approach of RNA-seq transcript normalization
BMC Bioinformatics, 2021 Background Normalization of RNA-seq data aims at identifying biological expression differentiation between samples by removing the effects of unwanted confounding factors.
Yance Feng, Lei M. Li
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The multivariate least-trimmed squares estimator
Journal of Multivariate Analysis, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Agulló, Jose +2 more
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