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A Monte Carlo Study Of Least Squares Parameter Estimation For The Learning Curve Equation
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Book Synopsis A Monte Carlo Study of Least Squares Parameter Estimation for the Learning Curve Equation by : Charles A. Thomas (CAPT, USAF.)
Download or read book A Monte Carlo Study of Least Squares Parameter Estimation for the Learning Curve Equation written by Charles A. Thomas (CAPT, USAF.) and published by . This book was released on 1975 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Masters Theses in the Pure and Applied Sciences by : Wade H. Shafer
Download or read book Masters Theses in the Pure and Applied Sciences written by Wade H. Shafer and published by Springer Science & Business Media. This book was released on 2013-11-21 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Masters Theses in the Pure and Applied Sciences was first conceived, published, and dis· seminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) *at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dissemination phases of the ac· tivity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volume were handled by an international publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 20 (thesis year 1975) a total of 10,374 theses titles from 28 Canadian and 239 United States universities. We are sure that this broader base for theses titles reported will greatly enhance the value of this important annual reference work. The organization of Volume 20 is identical to that of past years. It consists of theses titles arranged by discipline and by university within each discipline.
Book Synopsis A Monte Carlo Study of a Non-linear Least Squares Procedure for Estimating the Parameters of Two Enzyme Kinetic Models by : Alfred Jerry Anderson
Download or read book A Monte Carlo Study of a Non-linear Least Squares Procedure for Estimating the Parameters of Two Enzyme Kinetic Models written by Alfred Jerry Anderson and published by . This book was released on 1971 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Application of Monte Carlo Methods to the Evaluation of Small Sample Properties of 3-stage Least Squares Procedure by : Jugal Kishore Sharma
Download or read book The Application of Monte Carlo Methods to the Evaluation of Small Sample Properties of 3-stage Least Squares Procedure written by Jugal Kishore Sharma and published by . This book was released on 1965 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Monte Carlo Study of Orthogonal Least Squares Estimators by : Suat-Hun Go
Download or read book A Monte Carlo Study of Orthogonal Least Squares Estimators written by Suat-Hun Go and published by . This book was released on 1970 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parametric Estimates by the Monte Carlo Method by : Gennadij Alekseevič Michajlov
Download or read book Parametric Estimates by the Monte Carlo Method written by Gennadij Alekseevič Michajlov and published by VSP. This book was released on 1999 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is devoted to the further development of parametric weight Monte Carlo estimates for solving linear and nonlinear integral equations, radiation transfer equations, and boundary value problems, including problems with random parameters. The use of these estimates leads to the construction of new, effective Monte Carlo methods for calculating parametric multiple derivatives of solutions and for the main eigenvalues. The book opens with an introduction on the theory of weight Monte Carlo methods. The following chapters contain new material on solving boundary value problems with complex parameters, mixed problems to parabolic equations, boundary value problems of the second and third kind, and some improved techniques related to vector and nonlinear Helmholtz equations. Special attention is given to the foundation and optimization of the global 'walk on grid' method for solving the Helmholtz difference equation. Additionally, new Monte Carlo methods for solving stochastic radiation transfer problems are presented, including the estimation of probabilistic moments of corresponding critical parameters.
Book Synopsis A Monte Carlo study of two robust alternatives to least squares regression estimation by :
Download or read book A Monte Carlo study of two robust alternatives to least squares regression estimation written by and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Monte Carlo Investigation of Three Different Estimation Methods in Multilevel Structural Equation Modeling Under Conditions of Data Nonnormality and Varied Sample Sizes by : Jimmy Byrd
Download or read book A Monte Carlo Investigation of Three Different Estimation Methods in Multilevel Structural Equation Modeling Under Conditions of Data Nonnormality and Varied Sample Sizes written by Jimmy Byrd and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of the study was to examine multilevel regression models in the context of multilevel structural equation modeling (SEM) in terms of accuracy of parameter estimates, standard errors, and fit indices in normal and nonnormal data under various sample sizes and differing estimators (maximum likelihood, generalized least squares, and weighted least squares). The finding revealed that the regression coefficients were estimated with little to no bias among the study design conditions investigated. However, the number of clusters (group level) appeared to have the greatest impact on bias among the parameter estimate standard errors at both level-1 and level-2. In small sample sizes (i.e., 300 and 500) the standard errors were negatively biased. When the number of clusters was 30 and cluster size was held at 10, the level-1 standard errors were biased downward by approximately 20% for the maximum likelihood and generalized least squares estimators, while the weighted least squares estimator produced level-1 standard errors that were negatively biased by 25%. Regarding the level-2 standard errors, the level-2 standard errors were biased downward by approximately 24% in nonnormal data, especially when the correlation among variables was fixed at .5 and kurtosis was held constant at 7. In this same setting (30 clusters with cluster size fixed at 10), when kurtosis was fixed at 4 and the correlation among variables was held at .7, both the maximum likelihood and generalized least squares estimators resulted in standard errors that were biased downward by approximately 11%. Regarding fit statistics, negative bias was noted among each of the fit indices investigated when the number of clusters ranged from 30 to 50 and cluster size was fixed at 10. The least amount of bias was associated with the maximum likelihood estimator in each of the data normality conditions examined. As sample size increased, bias decreased to near zero when the sample size was equal to or greater than 1,500 with similar results reported across estimation methods. Recommendations for the substantive researcher are presented and areas of future research are presented.
Book Synopsis A Monte Carlo Study of the Small Sample Properties of Herman O.A. Wold's Iterative Least Squares Technique for Estimating Simultaneous Linear Equations by : Eric E. Fisher
Download or read book A Monte Carlo Study of the Small Sample Properties of Herman O.A. Wold's Iterative Least Squares Technique for Estimating Simultaneous Linear Equations written by Eric E. Fisher and published by . This book was released on 1967 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sequential Monte Carlo Parameter Estimation for Differential Equations by : Andrea Arnold
Download or read book Sequential Monte Carlo Parameter Estimation for Differential Equations written by Andrea Arnold and published by . This book was released on 2014 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: A central problem in numerous applications is estimating the unknown parameters of a system of ordinary differential equations (ODEs) from noisy measurements of a function of some of the states at discrete times. Formulating this dynamic inverse problem in a Bayesian statistical framework, state and parameter estimation can be performed using sequential Monte Carlo (SMC) methods, such as particle filters (PFs) and ensemble Kalman filters (EnKFs).Addressing the issue of particle retention in PF-SMC, we propose to solve ODE systems within a PF framework with higher order numerical integrators which can handle stiffness and to base the choice of the innovation variance on estimates of discretization errors. Using linear multistep method (LMM) numerical solvers in this context gives a handle on the stability and accuracy of propagation, and provides a natural and systematic way to rigorously estimate the innovation variance via well-known local error estimates.We explore computationally efficient implementations of LMM PF-SMC by considering parallelized and vectorized formulations. While PF algorithms are known to be amenable to parallelization due to the independent propagation of each particle, by formulating the problem in a vectorized fashion, it is possible to arrive at an implementation of the method which takes full advantage of multiple processors.We employ a variation of LMM PF-SMC in estimating unknown parameters of a tracer kinetics model from sequences of real positron emission tomography scan data. A combination of optimization and statistical inference is utilized: nonlinear least squares finds optimal starting values, which then act as hyperparameters in the Bayesian framework. The LMM PF-SMC algorithm is modified to allow variable time steps to accommodate the increase in time interval length between data measurements from beginning to end of the procedure, keeping the time step the same for each particle.We also apply the idea of linking innovation variance with numerical integration error estimates to EnKFs by employing a stochastic interpretation of the discretization error in numerical integrators, extending the technique to deterministic, large-scale nonlinear evolution models. The resulting algorithm, which introduces LMM time integrators into the EnKF framework, proves especially effective in predicting unmeasured system components.
Author :Matthew S. Goldberg Publisher :Institute for Operations Research and Management Sciences Nf ISBN 13 : Total Pages :200 pages Book Rating :4.3/5 (97 download)
Book Synopsis Statistical Methods for Learning Curves and Cost Analysis by : Matthew S. Goldberg
Download or read book Statistical Methods for Learning Curves and Cost Analysis written by Matthew S. Goldberg and published by Institute for Operations Research and Management Sciences Nf. This book was released on 2003 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: operations research and management science
Book Synopsis A Monte Carlo Study of Two Robust Alternatives of Least Square Regression Estimation by : Richard W. Hill
Download or read book A Monte Carlo Study of Two Robust Alternatives of Least Square Regression Estimation written by Richard W. Hill and published by . This book was released on 1974 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We give some Monte Carlo results on the performance of two robust alternatives to least squares regression estimation - least absolute residuals and the one-step "sine" estimator. We show how to scale the residuals for the sine estimator to achieve constant efficiency at the Gaussian across various choices of X-matrix and give some results for the contaminated Gaussian distribution.
Book Synopsis A Monte Carlo Study of Estimates of Simultaneous Linear Structural Equations by : Harvey M. Wagner
Download or read book A Monte Carlo Study of Estimates of Simultaneous Linear Structural Equations written by Harvey M. Wagner and published by . This book was released on 1954 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Monte Carlo Study of the Estimation of an Overidentified Model with Temporally Dependent Residuals by : Jean Pierre Aubry
Download or read book A Monte Carlo Study of the Estimation of an Overidentified Model with Temporally Dependent Residuals written by Jean Pierre Aubry and published by . This book was released on 1973 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Two-Stage Least Squares by : Sudhanshu K. Mishra
Download or read book Robust Two-Stage Least Squares written by Sudhanshu K. Mishra and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Two-Stage Least Squares (2-SLS) is a well known econometric technique used to estimate the parameters of a multi-equation (or simultaneous equations) econometric model when errors across the equations are not correlated and the equation(s) concerned is (are) over-identified or exactly identified. However, in presence of outliers in the data matrix, the classical 2-SLS has a very poor performance. In this study a method has been proposed to conveniently generalize the 2-SLS to the weighted 2-SLS (W2-SLS), which is robust to the effects of outliers and perturbations in the data matrix. Monte Carlo experiments have been conducted to demonstrate the performance of the proposed method. It has been found that robustness of the proposed method is not much destabilized by the magnitude of outliers, but it is sensitive to the number of outliers/perturbations in the data matrix. The breakdown point of the method is quite high, somewhere between 45 to 50 percent of the number of points in the data matrix.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1990 with total page 976 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author :Jian Yang Publisher :London : Department of Economics, University of Western Ontario ISBN 13 : Total Pages :68 pages Book Rating :4.:/5 (318 download)
Book Synopsis Semiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and Monte Carlo Evidence by : Jian Yang
Download or read book Semiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and Monte Carlo Evidence written by Jian Yang and published by London : Department of Economics, University of Western Ontario. This book was released on 1997 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
