Results 241 to 250 of about 1,640,518 (270)

Distributed Least Absolute Deviations Estimation

Journal of Guidance, Control, and Dynamics
Distributed algorithms are essential for reducing communication costs, computational complexity, and memory requirements while performing collaborative estimation using multi-agent systems. Additionally, robustness in estimators is important to prevent performance degradation when the measurement noise is non-Gaussian.
Kaushik Prabhu, Kyle T. Alfriend, Amir Rahmani, Fred Y. Hadaegh   +3 more
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Mean–Absolute Deviation Model

2010
We will survey important properties of the mean–absolute deviation (MAD) portfolio optimization model, which was introduced in 1990 to cope with very large–scale portfolio optimization problems. MAD model has been used for solving huge portfolio optimization models including internationally diversified investment model, long-term ALM model, mortgage ...
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The Absolute Deviation Correlation Coefficient

Perceptual and Motor Skills, 1982
A number of robust absolute deviation (AD) statistics have been developed recently. Two such correlation coefficients are developed and discussed, one for ranked data and another for interval level data. The standard error and range of the coefficients are given.
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55. Mean Absolute Deviation and Standard Deviation

At bottom, both MAD and S measure how far, on average, individual observations lie from the sample’s central tendency. 
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LEAST ABSOLUTE DEVIATIONS REGRESSION UNDER NONSTANDARD CONDITIONS

Econometric Theory, 2001
Most work on the asymptotic properties of least absolute deviations (LAD) estimators makes use of the assumption that the common distribution of the disturbances has a density that is both positive and finite at zero. We consider the implications of weakening this assumption in a number of regression settings, primarily with a time series ...
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Credibilistic Mean-Absolute Deviation Model

2016
Mean-absolute deviation model was first proposed by Konno and Yamazaki (1991) for stochastic portfolio optimization by using absolute deviation risk function to replace variance. It removes most of the difficulties associated with Markowitz’s mean-variance model.
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Least Absolute Deviation

2021
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Least Absolute Deviations

1984
Peter Bloomfield, William L. Steiger
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Mean-absolute deviation model

IIE Transactions, 2005
Hiroshi Konno, Tomoyuki Koshizuka
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Absolute Deviation

2005
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