Results 11 to 20 of about 1,208,864 (273)
M-estimation in high-dimensional linear model
Journal of Inequalities and Applications, 2018 We mainly study the M-estimation method for the high-dimensional linear regression model and discuss the properties of the M-estimator when the penalty term is a local linear approximation. In fact, the M-estimation method is a framework which covers the
Kai Wang, Yanling Zhu
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JMASM42: An Alternative Algorithm and Programming Implementation for Least Absolute Deviation Estimator of the Linear Regression Models (R) [PDF]
, 2016 We propose a least absolute deviation estimation method that produced a least absolute deviation estimator of parameter of the linear regression model.
Mbegbu, J. I. +2 more
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Croatian Operational Research Review, 2014 Motivated by the method for color image segmentation based on intensity and hue clustering proposed in [26] we give some theoretical explanations for this method that directly follows from the natural connection between the maximum likelihood approach ...
Petar Taler, Kristian Sabo
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Least absolute deviation estimation for unit root processes with garch errors [PDF]
, 2009 This paper considers a local least absolute deviation estimation for unit root processes with generalized autoregressive conditional heteroskedastic (GARCH) errors and derives its asymptotic properties under only finite second-order moment for both ...
Li, G, Li, WK
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A Maximum Likelihood Approach to Least Absolute Deviation Regression
EURASIP Journal on Advances in Signal Processing, 2004 Least absolute deviation (LAD) regression is an important tool used in numerous applications throughout science and engineering, mainly due to the intrinsic robust characteristics of LAD.
Yinbo Li, Gonzalo R. Arce
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Least Absolute Deviation Estimate for Functional Coefficient Partially Linear Regression Models
Journal of Probability and Statistics, 2012 The functional coefficient partially linear regression model is a useful generalization of the nonparametric model, partial linear model, and varying coefficient model.
Yanqin Feng, Guoxin Zuo, Li Liu
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IEEE Access, 2018 In order to solve the system identification problems, the normalized least mean absolute deviation (NLMAD) algorithm was developed as an effective and robust method. In this paper, aiming at the system identification problems with sparsity characteristic,
Wentao Ma +4 more
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Forecasting fiscal variables in selected European economies using least absolute deviation method
International Journal of Engineering Business Management, 2018 Actual economic crisis initiated numerous debates on fiscal policy of the European Union (EU) and unrealistic convergence demands placed upon the Member States, where the emphasis is on fiscal criteria: The budget deficit should not exceed 3% of Gross ...
Maja Mihelja Žaja +2 more
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Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
مجلة بغداد للعلوم, 2020 The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data.
Omar Abdulmohsin Ali, Ali Hameed Yousef
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E-Jurnal Matematika, 2017 Outliers are observations that are far away from other observations. Outlier can be interfered with the process of data analysis which influence the regression parameters estimation.
NI LUH PUTU RATNA KUMALASARI +2 more
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