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Parameter Estimation In Data Fitting With Special Application To Gaussian And Exponential Models
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Book Synopsis Parameter Estimation in Data Fitting, with Special Application to Gaussian and Exponential Models by : Emilio Spedicato
Download or read book Parameter Estimation in Data Fitting, with Special Application to Gaussian and Exponential Models written by Emilio Spedicato and published by . This book was released on 1977 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parameter estimation in data fitting, with special application to gaussian and exponential models by : E. Spedicato
Download or read book Parameter estimation in data fitting, with special application to gaussian and exponential models written by E. Spedicato and published by . This book was released on 1977 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parameter Estimation in Reliability and Life Span Models by : A Clifford Cohen
Download or read book Parameter Estimation in Reliability and Life Span Models written by A Clifford Cohen and published by CRC Press. This book was released on 2020-07-26 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers an applications-oriented treatment of parameter estimation from both complete and censored samples; contains notations, simplified formats for estimates, graphical techniques, and numerous tables and charts allowing users to calculate estimates and analyze sample data quickly and easily. Anno
Book Synopsis Exponential Data Fitting and Its Applications by : Victor Pereyra
Download or read book Exponential Data Fitting and Its Applications written by Victor Pereyra and published by Bentham Science Publishers. This book was released on 2010 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Real and complex exponential data fitting is an important activity in many different areas of science and engineering, ranging from Nuclear Magnetic Resonance Spectroscopy and Lattice Quantum Chromodynamics to Electrical and Chemical Engineering, Vision a"
Book Synopsis Some Applications of Optimization Methods by : Khizar Hayat Khan
Download or read book Some Applications of Optimization Methods written by Khizar Hayat Khan and published by . This book was released on 1995 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main concern of this research has been the application of optimization methods. We have surveyed different unconstrained optimization methods such as region elimination methods, function comparison methods, conjugate gradient methods (Fletcher-Reeves) and variable metric (Davidon-Fletcher-Powell; DFP, Broyden-Fletcher-Goldfarb-Shanno; BFGS) optimization methods. Maximizing the likelihood function L(theta) or equivalently, minimizing the function G(theta) = - ln(L(theta) falls in the area of optimization techniques. In this thesis we have applied different optimization techniques to different optimization problems. We have considered G(theta) to find the parameter estimates and the variance-covariance matrices of different probability distribution models. For the analysis of survival data and parameter estimation, we used variable metric (DFP and BFGS) optimization methods. The main advantage of these optimization methods is that the user can find the maximum of the log-likelihood function and the variance-covariance matrix of the parameter estimates, without computing second-order derivatives of the function. We have considered exponential, gamma, Gompertz, Gumbel, logistic, log-logistic, Pareto and Weibull distribution models. The application of the normal integral to log-normal and inverse Gaussian distribution models has also been considered for parameter estimation. In this thesis, the method of least squares has also been used for different probability distribution models for finding the parameter estimates and the variance-covariance matrices and is used as an alternative of the maximum likelihood estimation method.
Book Synopsis Parameter Estimation for Superimposed Weighted Exponentials by : Edward A. Ingham
Download or read book Parameter Estimation for Superimposed Weighted Exponentials written by Edward A. Ingham and published by . This book was released on 1996-07-01 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: The approach of modeling measured signals as superimposed exponentials in white Gaussian noise is popular and effective. However, estimating the parameters of the assumed model is challenging, especially when the data record length is short, the signal strength is low, or the parameters are closely spaced. In this dissertation, we first review the most effective parameter estimation scheme for the superimposed exponential model: maximum likelihood. We then provide a historical review of the linear prediction approach to parameter estimation for the same model. After identifying the improvements made to linear prediction and demonstrating their weaknesses, we introduce a completely tractable and statistically sound modification to linear prediction that we call iterative generalized least squares. It is shown, that our algorithm works to minimize the exact maximum likelihood cost function for the superimposed exponential problem and is therefore, equivalent to the previously developed maximum likelihood approach. However, our algorithm is indeed linear prediction, and thus revives a methodology previously categorized as inferior to maximum likelihood. With our modification, the insight provided by linear prediction can be carried to actual applications. We demonstrate this by developing an effective algorithm for deep level transient spectroscopy analysis. The signal of deep level transient spectroscopy is not a straight forward superposition of exponentials. However, with our methodology, an estimator, based on the exact maximum likelihood cost function for the actual signal, is quickly derived. At the end of the dissertation, we verify that our estimator extends the current capabilities of deep level transient spectroscopy analysis.
Book Synopsis Practical Longitudinal Data Analysis by : David J. Hand
Download or read book Practical Longitudinal Data Analysis written by David J. Hand and published by Routledge. This book was released on 2017-10-06 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.
Book Synopsis Fitting Models to Biological Data Using Linear and Nonlinear Regression by : Harvey Motulsky
Download or read book Fitting Models to Biological Data Using Linear and Nonlinear Regression written by Harvey Motulsky and published by Oxford University Press. This book was released on 2004-05-27 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Book Synopsis Generalized Estimating Equations by : James W. Hardin
Download or read book Generalized Estimating Equations written by James W. Hardin and published by CRC Press. This book was released on 2012-12-10 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Estimating Equations, Second Edition updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, al
Book Synopsis Estimation Techniques for Distributed Parameter Systems by : H.T. Banks
Download or read book Estimation Techniques for Distributed Parameter Systems written by H.T. Banks and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research detailed in this monograph was originally motivated by our interest in control problems involving partial and delay differential equations. Our attempts to apply control theory techniques to such prob lems in several areas of science convinced us that in the need for better and more detailed models of distributed/ continuum processes in biology and mechanics lay a rich, interesting, and challenging class of fundamen tal questions. These questions, which involve science and mathematics, are typical of those arising in inverse or parameter estimation problems. Our efforts on inverse problems for distributed parameter systems, which are infinite dimensional in the most common realizations, began about seven years ago at a time when rapid advances in computing capabilities and availability held promise for significant progress in the development of a practically useful as well as theoretically sound methodology for such problems. Much of the research reported in our presentation was not begun when we outlined the plans for this monograph some years ago. By publishing this monograph now, when only a part of the originally intended topics are covered (see Chapter VII in this respect), we hope to stimulate the research and interest of others in an area of scientific en deavor which has exceeded even our optimistic expectations with respect to excitement, opportunity, and stimulation. The computer revolution alluded to above and the development of new codes allow one to solve rather routinely certain estimation problems that would have been out of the question ten years ago.
Book Synopsis Classification, Parameter Estimation and State Estimation by : Ferdinand van der Heijden
Download or read book Classification, Parameter Estimation and State Estimation written by Ferdinand van der Heijden and published by John Wiley & Sons. This book was released on 2005-06-10 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is written and owned by one of the co-authors, B. Duin of the Delft University of Technology. After an introductory chapter, the book provides the theoretical construction for classification, estimation and state estimation. The book also deals with the skills required to bring the theoretical concepts to practical systems, and how to evaluate these systems. Together with the many examples in the chapters, the book is accompanied by a MATLAB toolbox for pattern recognition and classification. The appendix provides the necessary documentation for this toolbox as well as an overview of the most useful functions from these toolboxes. With its integrated and unified approach to classification, parameter estimation and state estimation, this book is a suitable practical supplement in existing university courses in pattern classification, optimal estimation and data analysis. Covers all contemporary main methods for classification and estimation. Integrated approach to classification, parameter estimation and state estimation Highlights the practical deployment of theoretical issues. Provides a concise and practical approach supported by MATLAB toolbox. Offers exercises at the end of each chapter and numerous worked out examples. PRtools toolbox (MATLAB) and code of worked out examples available from the internet Many examples showing implementations in MATLAB Enables students to practice their skills using a MATLAB environment
Book Synopsis Parameter Estimation for Scientists and Engineers by : Adriaan van den Bos
Download or read book Parameter Estimation for Scientists and Engineers written by Adriaan van den Bos and published by John Wiley & Sons. This book was released on 2007-08-03 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is estimating parameters of expectation models of statistical observations. The book describes the most important aspects of the subject for applied scientists and engineers. This group of users is often not aware of estimators other than least squares. Therefore one purpose of this book is to show that statistical parameter estimation has much more to offer than least squares estimation alone. In the approach of this book, knowledge of the distribution of the observations is involved in the choice of estimators. A further advantage of the chosen approach is that it unifies the underlying theory and reduces it to a relatively small collection of coherent, generally applicable principles and notions.
Book Synopsis Contemporary Statistical Models for the Plant and Soil Sciences by : Oliver Schabenberger
Download or read book Contemporary Statistical Models for the Plant and Soil Sciences written by Oliver Schabenberger and published by CRC Press. This book was released on 2001-11-13 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite its many origins in agronomic problems, statistics today is often unrecognizable in this context. Numerous recent methodological approaches and advances originated in other subject-matter areas and agronomists frequently find it difficult to see their immediate relation to questions that their disciplines raise. On the other hand, statisticians often fail to recognize the riches of challenging data analytical problems contemporary plant and soil science provides. The first book to integrate modern statistics with crop, plant and soil science, Contemporary Statistical Models for the Plant and Soil Sciences bridges this gap. The breadth and depth of topics covered is unusual. Each of the main chapters could be a textbook in its own right on a particular class of data structures or models. The cogent presentation in one text allows research workers to apply modern statistical methods that otherwise are scattered across several specialized texts. The combination of theory and application orientation conveys ìwhyî a particular method works and ìhowî it is put in to practice. About the downloadable resources The accompanying downloadable resources are a key component of the book. For each of the main chapters additional sections of text are available that cover mathematical derivations, special topics, and supplementary applications. It supplies the data sets and SAS code for all applications and examples in the text, macros that the author developed, and SAS tutorials ranging from basic data manipulation to advanced programming techniques and publication quality graphics. Contemporary statistical models can not be appreciated to their full potential without a good understanding of theory. They also can not be applied to their full potential without the aid of statistical software. Contemporary Statistical Models for the Plant and Soil Science provides the essential mix of theory and applications of statistical methods pertinent to research in life sciences.
Book Synopsis Data Assimilation and Control: Theory and Applications in Life Sciences by : Axel Hutt
Download or read book Data Assimilation and Control: Theory and Applications in Life Sciences written by Axel Hutt and published by Frontiers Media SA. This book was released on 2019-08-16 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: The understanding of complex systems is a key element to predict and control the system’s dynamics. To gain deeper insights into the underlying actions of complex systems today, more and more data of diverse types are analyzed that mirror the systems dynamics, whereas system models are still hard to derive. Data assimilation merges both data and model to an optimal description of complex systems’ dynamics. The present eBook brings together both recent theoretical work in data assimilation and control and demonstrates applications in diverse research fields.
Book Synopsis A Review of the Parameter Estimation Problem of Fitting Positive Exponential Sums to Empirical Data by :
Download or read book A Review of the Parameter Estimation Problem of Fitting Positive Exponential Sums to Empirical Data written by and published by . This book was released on 1998 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Inference by : Hanns L. Harney
Download or read book Bayesian Inference written by Hanns L. Harney and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving a longstanding problem in the physical sciences, this text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. The text is written at introductory level, with many examples and exercises.
Book Synopsis Linear and Nonlinear Regression With Matlab. Fitting Curves and Surfaces to Data by : Perez C.
Download or read book Linear and Nonlinear Regression With Matlab. Fitting Curves and Surfaces to Data written by Perez C. and published by . This book was released on 2017-08-17 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB allows to work with linear and nonlinear regression models efficiently. It has tools that contemplate the phases of estimation, diagnosis and prediction.MATLAB Curve Fitting Toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing.After creating a fit, you can apply a variety of post-processing methods for plotting,interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives.Curve Fitting Toolbox software allows you to work in two different environments:* An interactive environment, with the Curve Fitting app and the Spline Tool* A programmatic environment that allows you to write object-oriented MATLAB code using curve and surface fitting methodsThis book develops the following topics:* "Curve Fitting" * "Surface Fitting" * "Spline Fitting" * "Parametric Fitting with Library Models" * "Polynomial Models" * "Exponential Models" * "Fourier Series Models"* "Gaussian Models"* "Power Series Models"* "Rational Models"* "Sum of Sines Models"* "Weibull Distribution Models"* "Least-Squares Fitting"* "Linear Least Squares" * "Weighted Least Squares" * "Robust Least Squares" * "Nonlinear Least Squares" * "Robust Fitting"* "Custom Linear and Nonlinear Regression" * "Nonparametric Fitting"* "Interpolation and Smoothing" * "Smoothing Splines"* "Filtering and Smoothing Data"* "Fit Postprocessing" * "Explore and Customize Plots" * "Remove Outliers" * "Select Validation Data" * "Evaluate a Curve Fit" * "Evaluate a Surface Fit"* "Compare Fits Programmatically" * "Evaluating Goodness of Fit"* "Residual Analysis" * "Confidence and Prediction Bounds"
