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Least absolute deviations estimation for the censored regression model
 Journal of Econometrics
, 1984
"... This paper proposes an alternative to maximum likelihood estimation of the parameters of the censored regression (or censored ‘Tobit’) model. The proposed estimator is a generalization of least absolute deviations estimation for the standard linear model, and, unlike estimation methods based on the ..."
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Cited by 285 (6 self)
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This paper proposes an alternative to maximum likelihood estimation of the parameters of the censored regression (or censored ‘Tobit’) model. The proposed estimator is a generalization of least absolute deviations estimation for the standard linear model, and, unlike estimation methods based
Analysis of least absolute deviation
"... The least absolute deviation or L1 method is a widely known alternative to the classical least squares or L2 method for statistical analysis of linear regression models. Instead of minimizing the sum of squared errors, it minimizes the sum of absolute values of errors. Despite its long history and m ..."
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Cited by 3 (1 self)
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The least absolute deviation or L1 method is a widely known alternative to the classical least squares or L2 method for statistical analysis of linear regression models. Instead of minimizing the sum of squared errors, it minimizes the sum of absolute values of errors. Despite its long history
Estimation Noise in Portfolio Optimization with Absolute Deviation
, 2004
"... Portfolio selection has a central role in finance theory and practical applications. The classical approach uses the standard deviation (variance) as risk measure, while several other alternatives have also been introduced in the literature. Due to its computational advantages, portfolio optimizat ..."
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optimization based on absolute deviation looks particularly interesting and it is widely used in practice. For the practical implementation of any variant, however, one needs to estimate the parameters from finite return series, which inevitably introduces measurement noise that in turn affects the portfolio
Bahadur Representations for the Median Absolute Deviation and Its Modifications
, 2009
"... The median absolute deviation about the median (MAD) is an important univariate spread measure having wide appeal due to its highly robust sample version. A powerful tool in treating the asymptotics of a statistic is a linearization, i.e., a Bahadur representation. Here we establish both strong and ..."
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Cited by 2 (1 self)
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The median absolute deviation about the median (MAD) is an important univariate spread measure having wide appeal due to its highly robust sample version. A powerful tool in treating the asymptotics of a statistic is a linearization, i.e., a Bahadur representation. Here we establish both strong
Fuzzy linear regression based on least absolute deviations
 Iranian J. fuzzy system
, 2012
"... Abstract. This study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. A least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. The proposed approach, which can ..."
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Cited by 2 (0 self)
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Abstract. This study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. A least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. The proposed approach, which
On the weighting of the meanabsolutedeviation cost minimization model On the weighting of the meanabsolutedeviation cost minimization model
, 2013
"... Abstract The meanabsolutedeviation cost minimization model, which aims to minimize sum of the mean value and the absolute deviation (AD) of the total cost multiplied by a given nonnegative weighting, is one of a number of typical robust optimization models. This paper first uses a straightforwar ..."
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Abstract The meanabsolutedeviation cost minimization model, which aims to minimize sum of the mean value and the absolute deviation (AD) of the total cost multiplied by a given nonnegative weighting, is one of a number of typical robust optimization models. This paper first uses a
2007b). Tuning parameter selectors for the smoothly clipped absolute deviation method
 Biometrika
"... The penalised least squares approach with smoothly clipped absolute deviation penalty has been consistently demonstrated to be an attractive regression shrinkage and selection method. It not only automatically and consistently selects the important variables, but also produces estimators which are ..."
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Cited by 78 (11 self)
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The penalised least squares approach with smoothly clipped absolute deviation penalty has been consistently demonstrated to be an attractive regression shrinkage and selection method. It not only automatically and consistently selects the important variables, but also produces estimators which
Analysis of Mean Absolute Deviation for Randomized Block Design under Laplace Distribution
"... Abstract: Analysis of mean absolute deviation (ANOMAD) for randomized block design is derived where the total sum of absolute deviation (TSA) is partition into exact block sum of absolute deviation (BLSA), exact treatment sum of absolute deviation (TRSA) and within sum of absolute deviation (WSA). T ..."
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Abstract: Analysis of mean absolute deviation (ANOMAD) for randomized block design is derived where the total sum of absolute deviation (TSA) is partition into exact block sum of absolute deviation (BLSA), exact treatment sum of absolute deviation (TRSA) and within sum of absolute deviation (WSA
Instrumental Variable Estimation Based on Mean Absolute Deviation
, 2001
"... this paper. 2 An estimator based on this approach can be defined as the maximizer of the sample analogue of Q. We can form various estimators by taking various dispersion measures in Q. A leading example of the dispersion measure is the standard deviation. The function Q with the standard deviation ..."
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Cited by 5 (3 self)
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this paper. 2 An estimator based on this approach can be defined as the maximizer of the sample analogue of Q. We can form various estimators by taking various dispersion measures in Q. A leading example of the dispersion measure is the standard deviation. The function Q with the standard deviation
MEANABSOLUTE DEVIATION PORTFOLIO SELECTION MODEL WITH FUZZY RETURNS
, 2011
"... Abstract. In this paper, we consider portfolio selection problem in which security returns are regarded as fuzzy variables rather than random variables. We first introduce a concept of absolute deviation for fuzzy variables and prove some useful properties, which imply that absolute deviation may b ..."
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Abstract. In this paper, we consider portfolio selection problem in which security returns are regarded as fuzzy variables rather than random variables. We first introduce a concept of absolute deviation for fuzzy variables and prove some useful properties, which imply that absolute deviation may
Results 1  10
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1,523