A Proposal for the Estimation of Parameters of Simultaneous Non Linear Equations Systems PDF Download
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Author: J. P. Ancot
Publisher:
ISBN:
Category :
Languages : en
Pages : 50
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Book Description
Author: J. P. Ancot
Publisher:
ISBN:
Category :
Languages : en
Pages : 50
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Book Description
Author: Stephen M. Goldfeld
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 52
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Book Description
The small sample properties of certain estimators of the coefficients of systems of simultaneous nonlinear equations are investigated. Sampling experiments are used in connection with two specific nonlinear models. The estimating methods investigated comprise direct least squares, various forms of two-stage least squares and full-information maximum likelihood. The relative performances of the various methods are evaluated on the basis of informal comparisons of their respective mean absolute errors and root mean square errors and also by more formal tests of significance. Direct least squares is found to be, as expected, the worst estimating method. The other two methods are rather more comparable with full-information maximum likelihood holding the edge for both theoretical and experimental reasons. (Author).
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Category : Weights and measures
Languages : en
Pages : 574
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Author: Anthony McNeil Jackson
Publisher:
ISBN:
Category :
Languages : en
Pages : 288
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Author:
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Category : City Planning
Languages : en
Pages : 904
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Author:
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ISBN:
Category : Regional planning
Languages : en
Pages : 180
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Author: Markku T. Nihtilä
Publisher:
ISBN: 9789517509961
Category :
Languages : en
Pages : 41
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Book Description
Author: Hrishikesh D Vinod
Publisher: World Scientific
ISBN: 9811256195
Category : Business & Economics
Languages : en
Pages : 645
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Book Description
How to learn both applied statistics (econometrics) and free, open-source software R? This book allows students to have a sense of accomplishment by copying and pasting many hands-on templates provided here.The textbook is essential for anyone wishing to have a practical understanding of an extensive range of topics in Econometrics. No other text provides software snippets to learn so many new statistical tools with hands-on examples. The explicit knowledge of inputs and outputs of each new method allows the student to know which algorithm is worth studying. The book offers sufficient theoretical and algorithmic details about a vast range of statistical techniques.The second edition's preface lists the following topics generally absent in other textbooks. (i) Iteratively reweighted least squares, (ii) Pillar charts to represent 3D data. (iii) Stochastic frontier analysis (SFA) (iv) model selection with Mallows' Cp criterion. (v) Hodrick-Prescott (HP) filter. (vi) Automatic ARIMA models. (vi) Nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals. (vii) new Keynesian Phillips curve (NKPC). (viii) Market-neutral pairs trading using two cointegrated stocks. (ix) Artificial neural network (ANN) for product-specific forecasting. (x) Vector AR and VARMA models. (xi) New tools for diagnosing the endogeneity problem. (xii) The elegant set-up of k-class estimators and identification. (xiii) Probit-logit models and Heckman selection bias correction. (xiv) Receiver operating characteristic (ROC) curves and areas under them. (xv) Confusion matrix. (xvi) Quantile regression (xvii) Elastic net estimator. (xviii) generalized Correlations (xix) maximum entropy bootstrap for time series. (xx) Convergence concepts quantified. (xxi) Generalized partial correlation coefficients (xxii) Panel data and duration (survival) models.
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Category : GAUSS (Computer program)
Languages : en
Pages : 22
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Book Description
Solves systems of nonlinear equations having as many equations as unknowns.
Author: Harvey Motulsky
Publisher: Oxford University Press
ISBN: 9780198038344
Category : Mathematics
Languages : en
Pages : 352
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Book Description
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.
