Results 1  10
of
14
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 246 (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 on the assumption of normally distributed error terms, the estimator is consistent and asymptotically normal for a wide class of error distributions, and is also robust to heteroscedasticity. The paper gives the regularity conditions and proofs of these largesample results, and proposes classes of consistent estimators of the asymptotic ovariance matrix for both homoscedastic and heteroscedastic disturbances. 1.
An Efficient Constraint Handling Method for Genetic Algorithms
 Computer Methods in Applied Mechanics and Engineering
, 1998
"... Many realworld search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods hav ..."
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Cited by 188 (14 self)
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Many realworld search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods have been the most popular approach, because of their simplicity and ease of implementation. However, since the penalty function approach is generic and applicable to any type of constraint (linear or nonlinear), their performance is not always satisfactory. Thus, researchers have developed sophisticated penalty functions specific to the problem at hand and the search algorithm used for optimization. However, the most difficult aspect of the penalty function approach is to find appropriate penalty parameters needed to guide the search towards the constrained optimum. In this paper, GA's populationbased approach and ability to make pairwise comparison in tournament selection operator are explo...
LARGESCALE LINEARLY CONSTRAINED OPTIMIZATION
, 1978
"... An algorithm for solving largescale nonlinear ' programs with linear constraints is presented. The method combines efficient sparsematrix techniques as in the revised simplex method with stable quasiNewton methods for handling the nonlinearities. A generalpurpose production code (MINOS) is ..."
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Cited by 102 (17 self)
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An algorithm for solving largescale nonlinear ' programs with linear constraints is presented. The method combines efficient sparsematrix techniques as in the revised simplex method with stable quasiNewton methods for handling the nonlinearities. A generalpurpose production code (MINOS) is described, along with computational experience on a wide variety of problems.
The crossentropy method for continuous multiextremal optimization
 Methodology and Computing in Applied Probability
"... Abstract In recent years, the crossentropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the crossentropy method in the context of continuous optimization. We demonstrate the effectiveness of the crossentropy method for solving diffi ..."
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Cited by 27 (5 self)
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Abstract In recent years, the crossentropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the crossentropy method in the context of continuous optimization. We demonstrate the effectiveness of the crossentropy method for solving difficult continuous multiextremal optimization problems, including those with nonlinear constraints.
Interior point algorithms for nonlinear least squares problems
 Inverse Problems in Science and Engineering
"... jose @ optimize.ufrj.br veranise @ optimize.ufrj.br ..."
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Cited by 3 (2 self)
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jose @ optimize.ufrj.br veranise @ optimize.ufrj.br
A norm descent BFGS method for solving KKT systems of symmetric variational inequality problems, Optimization Methods and
 Software
"... In this article, the KKT system of the variational inequality problem is reformulated as a nonsmooth equation. On the basis of this reformulation, a norm descent BFGS method is proposed. The method is globally and superlinearly convergent. ..."
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Cited by 1 (1 self)
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In this article, the KKT system of the variational inequality problem is reformulated as a nonsmooth equation. On the basis of this reformulation, a norm descent BFGS method is proposed. The method is globally and superlinearly convergent.
I)ISCRETION IN TIIF CHOICE OF MACROECONOMIC POLICIES
"... This paper explores the quantitative implications for uggreg(zr( ' economic performance and stability of cinulueting a discretionary pohet ' developed from the theory of feedback control of stochwtc 5)5 ferns. The control.ccherne applied here partitions the polky problem into a determinist ..."
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This paper explores the quantitative implications for uggreg(zr( ' economic performance and stability of cinulueting a discretionary pohet ' developed from the theory of feedback control of stochwtc 5)5 ferns. The control.ccherne applied here partitions the polky problem into a deterministic planning problem and a stochasin ' stabilization problem. The results indicate that.sigiithcant gains are arailahh ' from a discretionart ' policy acer a nondiscretionary policy of fixed instrwnent choices. Whether macroeconomic policy for the United States should admit an clement of discretion has been an issue among economists for over a decade, and is recognized as one of the principal elements of the monetaristfiscalist debate. The question has typically been addressed by characterizing the dynamic aspects of the American economy and then asking whether the performance of an econdmy with such characteristics could be improved by allowing discretionary changes in policy choices from time to time. For example, in his recent review article Leonall Andersen (1973) notes the fisc'.alist view that exogenous disturbances of the economy "lead necessarily to recurring fluctuations in output and prices which are of a cyclical nature, " and the fiscalist belief that "there does not exist
Analysis of onedimensional seismic waveform inversion by Regularized Global Approximation
, 1995
"... Direct analysis of normal incidence seismogram inversion with respect to a velocity profile is available now due to applying of a new global optimization algorithm. The latter is based upon regularized global approximation of an objective function which is not supposed to be differentiable. The new ..."
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Direct analysis of normal incidence seismogram inversion with respect to a velocity profile is available now due to applying of a new global optimization algorithm. The latter is based upon regularized global approximation of an objective function which is not supposed to be differentiable. The new technique allows to see clearly a nonuniqueness of the inversion problem, no matter how high is a quality of the input data. It is induced by a few factors: a source wavelet is a function of a finite frequency band, an effective wave length of the sounding signal is increasing jointly with the velocity, and the power of a media response is decreasing with respect to the depth. The nonuniqueness means that there is no inversion/processing enable to solve the problem if it does not take into account a priori information about the recovered velocity profile. It is shown how an a priori assumption about a trend of the profile can essentially reduce the nonuniqueness of the problem. The correspon...