Book ChapterDOI
Response Surface Methodology in Risk Analysis
L. Olivi
- pp 313-327
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TLDR
The Response Surface Methodology (RSM) as mentioned in this paper is a general approach to system identification that organises several statistical techniques in order to provide an estimate of the p.d.Abstract:
The Response Surface Methodology as a general approach to the system identification is presented. The method organises several statistical techniques in order to provide an estimate of the p.d.f. of the output variable of the identified system as a function of the p.d.f.’s of the input variable, as the final result. In particular the following techniques are dealt with:
the sensitivity analysis;
the choice of the approximating function;
the experimental design;
the parameter estimation.
A typical application is provided.read more
Citations
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BookDOI
Handbook of Simulation
Eric R. Ziegel,Jerry Banks +1 more
TL;DR: The Abstract Object class defines and characterizes all the essential properties every class in this design has in this 404 OBJECT-ORIENTED SIMULATION.
Journal ArticleDOI
Response surface methodology: 1966–1988
TL;DR: This article reviews the progrrss of RSM in the general areas of experimental design and analysis and indicates how its role has been affected by advanccs in other fields of applied statistics.
Journal ArticleDOI
High-order limit state functions in the response surface method for structural reliability analysis
Henri P. Gavin,Siu Chung Yau +1 more
TL;DR: In this article, the use of higher order polynomials is proposed to approximate the true limit state more accurately, which is a technique for the reliability analysis of complex systems with low failure probabilities.
Journal ArticleDOI
Response Surface Methodology for Constrained Simulation Optimization: an Overview
TL;DR: GRSM allows multiple random responses, selecting one response as goal and the other responses as constrained variables, and combines these gradients with Mathematical Programming findings to estimate a better search direction than the steepest ascent direction used by RSM.
Journal ArticleDOI
Performance and reliability of semi-active equipment isolation
Henri P. Gavin,A. Zaicenco +1 more
TL;DR: In this article, the authors examined the performance and reliability of passive and semi-active damping in equipment isolation systems for earthquake protection and compared the performance for historical earthquakes and for a set of different building models.
References
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Book ChapterDOI
On the Experimental Attainment of Optimum Conditions
George E. P. Box,K. B. Wilson +1 more
TL;DR: The work described in this article is the result of a study extending over the past few years by a chemist and a statistician, which has come about mainly in answer to problems of determining optimum conditions in chemical investigations, but they believe that the methods will be of value in other fields where experimentation is sequential and the error fairly small.
Journal ArticleDOI
Ridge Regression: Applications to Nonorthogonal Problems
TL;DR: In this paper, the use of ridge regression methods is discussed and recommendations are made for obtaining a better regression equation than that given by ordinary least squares estimation. But the authors focus on the RIDGE TRACE which is a two-dimensional graphical procedure for portraying the complex relationships in multifactor data.
Journal ArticleDOI
Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
TL;DR: In this article, the authors discuss a class of biased linear estimators employing generalized inverses and establish a unifying perspective on nonlinear estimation from nonorthogonal data.
Journal ArticleDOI
Ridge regression:some simulations
TL;DR: In this paper, an algorithm is given for acting the biasing paramatar, k, in RIDGE regrassion, which has the following properties: (i) it produces an aberaged squared error for the regression coafficiants that is les than least squares, (ii) the distribuction of squared arrots for the regressors has a smallar variance than does that for last squares, and (iii) regradless of he signal-to-noiss retio the probability that RIDge produces a smaller squared error than least square is
Journal ArticleDOI
The Equivalence of Two Extremum Problems
J. Kiefer,J. Wolfowitz +1 more
TL;DR: In this article, the authors consider the problem of defining probability measures with finite support, i.e., measures that assign probability one to a set consisting of a finite number of points.