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Exponential Probability Inequality and Convergence Results for the Median Absolute Deviation and Its Modifications
, 2009
"... The median absolute deviation from the median (MAD) is an important robust univariate spread measure. It also plays important roles with multivariate data through statistics based on the univariate projections of the data, in which case a modified sample MAD introduced ..."
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Cited by 4 (3 self)
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The median absolute deviation from the median (MAD) is an important robust univariate spread measure. It also plays important roles with multivariate data through statistics based on the univariate projections of the data, in which case a modified sample MAD introduced
ESTIMATION OF NUISANCE PARAMETERS FOR INFERENCE BASED ON LEAST ABSOLUTE DEVIATIONS
"... Abstract. Statistical inference procedures based on least absolute deviations involve estimates of a matrix which plays the role of a multivariate nuisance parameter. To estimate this matrix, we use kernel smoothing. We show consistency and obtain bounds on the rate of convergence. 1. Introduction. ..."
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Abstract. Statistical inference procedures based on least absolute deviations involve estimates of a matrix which plays the role of a multivariate nuisance parameter. To estimate this matrix, we use kernel smoothing. We show consistency and obtain bounds on the rate of convergence. 1. Introduction
MEAN ABSOLUTE DEVIATIONS OF SAMPLE MEANS AND MINIMALLY CONCENTRATED BINOMIALS
, 2003
"... This is a contribution to the theory of sums of independent random variables at the level of optimal explicit inequalities: we compute the optimal constants in Hornich’s lower bounds for the mean absolute deviations of sample means. This is done by reducing the original problem to the elementary o ..."
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Cited by 1 (0 self)
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This is a contribution to the theory of sums of independent random variables at the level of optimal explicit inequalities: we compute the optimal constants in Hornich’s lower bounds for the mean absolute deviations of sample means. This is done by reducing the original problem to the elementary
Premium calculation: Why standard deviation should be replaced by absolute deviation
 ASTIN Bulletin
, 1990
"... Average absolute (instead of quadratic) deviation from median (instead of expectation) is better suited to determine the safety loading for insurance premiums than standard eviation: The corresponding premium functionals behave additive under the practically relevant risk sharing schemes between fir ..."
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Cited by 21 (0 self)
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Average absolute (instead of quadratic) deviation from median (instead of expectation) is better suited to determine the safety loading for insurance premiums than standard eviation: The corresponding premium functionals behave additive under the practically relevant risk sharing schemes between
Least Absolute Deviations Estimation for the Accelerated Failure Time Model
, 2005
"... Summary The accelerated failure time (AFT) model assumes a linear relationship between the event time and the covariates. We propose a robust weighted leastabsolutedeviations (LAD) method for estimation in the AFT model with rightcensored data. This method uses the KaplanMeier weights in the LAD ..."
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Cited by 6 (3 self)
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Summary The accelerated failure time (AFT) model assumes a linear relationship between the event time and the covariates. We propose a robust weighted leastabsolutedeviations (LAD) method for estimation in the AFT model with rightcensored data. This method uses the KaplanMeier weights
Clusterwise Linear Regression with the Least Sum of Absolute Deviations – An MIP Approach
, 2012
"... Abstract ⎯ In this paper, we study the application of mixedinteger programming (MIP) to the clusterwise linear regression (CLR) problem with the least sum of absolute deviations, which is a type of CLR problem that has received both theoretical and practical interests in recent years. We formulate ..."
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Abstract ⎯ In this paper, we study the application of mixedinteger programming (MIP) to the clusterwise linear regression (CLR) problem with the least sum of absolute deviations, which is a type of CLR problem that has received both theoretical and practical interests in recent years. We formulate
Design of Recurrent Neural Networks for Solving Constrained Least Absolute Deviation Problems
"... Abstract—Recurrent neural networks for solving constrained least absolute deviation (LAD) problems or L1norm optimization problems have attracted much interest in recent years. But so far most neural networks can only deal with some special linear constraints efficiently. In this paper, two neural ..."
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Abstract—Recurrent neural networks for solving constrained least absolute deviation (LAD) problems or L1norm optimization problems have attracted much interest in recent years. But so far most neural networks can only deal with some special linear constraints efficiently. In this paper, two neural
Global Constraints for the Mean Absolute Deviation and the Variance: Application to the Vertical Line Balancing.
"... Optimization with a balancing objective often appear in practical problems where humans are implied in the solution. For example, in tasks assignment problems it is a desirable property that the workload is fairly distributed among the workers. In general, a violation measure of the perfect balance ..."
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can be defined as the Lp norm of the vector of variables minus their mean. Two global constraints are presented that can be used in constraint programming to optimize the criteria L1 (the mean absolute deviation) and L2 (the variance). These global constraints have been implemented in the Gecode
Mitigation of Multipath Errors Using the Iterative Least Absolute Deviation Approach
"... Abstract. The least squares (LS) approach has been widely used for solving the GPS navigation solution. Despite its many superior properties, however, the LS estimate can be sensitive to outliers and its performance in terms of accuracy and statistical inferences may be compromised when the errors a ..."
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are large and heterogeneous. The GPS signal is strongly affected by the multipath propagation errors. The LS is not able to cope with the above condition to provide a useful and plausible solution. In this paper, an alternative approach based on the least absolute deviation (LAD) criterion for estimating
FITTING A TAPER FUNCTION TO MINIMIZE THE SUM OF ABSOLUTE DEVIATIONS
"... ABSTRACT: Multiple product inventories of forests require accurate estimates of the diameter, length and volume of each product. Taper functions have been used to precisely describe tree form, once they provide estimates for the diameter at any height or the height at any diameter. This study applie ..."
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Cited by 2 (0 self)
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applied a goal programming technique to estimate the parameters of two taper functions to describe individual tree forms. The goal programming formulation generates parameters that minimize total absolute deviations (MOTAD). These parameters generated by the MOTAD method were compared to those of ordinary
Results 11  20
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584,745