0000000000341216

AUTHOR

P. Stahlecker

showing 4 related works from this author

ESL ? A New Simulation Language for Economic Models

1990

A new simulation language for modelling economic processes is presented which allows the specification of single decision units and coordinates all their activities. The basic ideas and features of this language will be described and demonstrated through small examples.

Computer sciencebusiness.industryEconomics Econometrics and Finance (miscellaneous)Economic modelArtificial intelligencebusinesscomputer.software_genreSoftware engineeringcomputerNatural language processingComputer Science ApplicationsSimulation languageComputer Science in Economics and Management
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Minimax estimation with additional linear restrictions - a simulation study

1988

Let the parameter vector of the ordinary regression model be constrained by linear equations and in addition known to lie in a given ellipsoid. Provided the weight matrix A of the risk function has rank one, a restricted minimax estimator exists which combines both types of prior information. For general n.n.d. A two estimators as alternatives to the unfeasible exact minimax estimator are developed by minimizing an upper and a lower bound of the maximal risk instead. The simulation study compares the proposed estimators with competing least-squares estimators where remaining unknown parameters are replaced by suitable estimates.

Statistics and ProbabilityMathematical optimizationRank (linear algebra)Modeling and SimulationLinear regressionStatisticsEstimatorMinimax estimatorMinimaxEllipsoidUpper and lower boundsLinear equationMathematicsCommunications in Statistics - Simulation and Computation
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Some properties of [tr(Q2p)]12p with application to linear minimax estimation

1990

Abstract A nondifferentiable minimization problem is considered which occurs in linear minimax estimation. This problem is solved by replacing the nondifferentiable maximal eigenvalue of a real nonnegative definite matrix Q with [tr( Q 2 p )] 1/2 p . It is shown that any descent algorithm with inexact step-length rule can be used to obtain linear minimax estimators for the parameter vector of a parameter-restricted linear model.

Discrete mathematicsNumerical AnalysisAlgebra and Number TheoryMinimization problemLinear modelMathematics::Optimization and ControlMinimaxMinimax approximation algorithmMatrix (mathematics)Discrete Mathematics and CombinatoricsGeometry and TopologyMinimax estimatorDescent algorithmEigenvalues and eigenvectorsMathematicsLinear Algebra and its Applications
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Linear and ellipsoidal restrictions in linear regression

1991

The problem of combining linear and ellipsoidal restrictions in linear regression is investigated. Necessary and sufficient conditions for compactness of the restriction set are proved assuring the existence of a minimax estimator. When the restriction set is not compact a minimax estimator may still exist for special loss functions arid regression designs

Statistics and ProbabilityPolynomial regressionStatistics::TheoryMathematical optimizationProper linear modelLinear predictor functionBayesian multivariate linear regressionLinear regressionLinear modelPrincipal component regressionStatistics Probability and UncertaintySimple linear regressionMathematicsStatistics
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