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This document is intended both as a tutorial guide for users not familiar with invar and as a reference manual for experienced users. New users should read the first 5 chapters before attempting to use the code.
Chapters 2 and 3 give the necessary information to write the user sup plied subroutines. Chapter 2 deals with writing the model in variable sepa rable form, while Chapter 3 describes the required fortran subroutines in detail.
Chapter 4 gives a brief description of the logic of the invar driver program. It should be read by beginning users before trying to execute the program.
Chapters 5, 9 and 10 give examples of real world modelling problems solved with invar, including output from actual terminal sessions. The problem in Chapter 5 is simpler than the other two. Chapter 9 describes a time-series modelling problem and Chapter 10 describes a problem with two independent variables.
Chapter 6 describes some Cyber 855 Procedures that can be used to execute invar at the National Bureau of Standards and will probably be of interest only to nbs users.
Chapter 7 gives detailed explanations of the prompts and messages that the user will encounter during the execution of invar. Most users should be able to get started with invar after reading Chapter 5, but might want to refer to Chapter 7 for more details on specific points. Many users will probably also refer quite often to Table which summarizes all of the invar command codes.
The statistical diagnostics generated by invar are described in Chapter 8, which is included for users who are not already familiar with the standard least squares diagnostic plots.
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An Interactive Nonlinear Least Squares Program (Classic Reprint)
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An Interactive Nonlinear Least Squares Program (Classic Reprint)
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Paperback. Condizione: New. Print on Demand. This book offers a solution to nonlinear least squares problems, an important technique for obtaining the most likely parameters in a model from experimental data. The approach outlined in this book separates the parameters into linear and non-linear, iterating only on the latter. This technique is advantageous over traditional methods, as it does not require initial guesses for linear parameters, typically improves convergence properties, and simplifies the coding required. The book provides a thorough exploration of the variable-separable nonlinear regression program VARPRO, which implements this technique. Extensive statistical diagnostics and plotting capabilities are also covered, aiding users in assessing the accuracy of their model fits. The book's insights will be valuable to scientists, engineers, and statisticians working with real-world modeling problems. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Codice articolo 9781528018906_0
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