A Compendium of Lake and Reservoir Data Collected by the National Eutrophication Survey in Eastern North-Central, and Southeastern United States. National Eutrophication Survey ; Corvallis Environmental Research Laboratory and Environmental Monitoring & Support Laboratory, Las Vegas, Nevada PDF Download
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Author: National Eutrophication Survey (U.S.)
Publisher:
ISBN:
Category : Eutrophication
Languages : en
Pages : 266
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Book Description
Author: National Eutrophication Survey (U.S.)
Publisher:
ISBN:
Category : Eutrophication
Languages : en
Pages : 266
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Book Description
Author:
Publisher:
ISBN:
Category : Hydrology
Languages : en
Pages : 968
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Book Description
Author: National Acid Precipitation Assessment Program (U.S.). Office of the Director
Publisher:
ISBN:
Category : Acid deposition
Languages : en
Pages : 70
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Book Description
Author:
Publisher:
ISBN:
Category : Water
Languages : en
Pages : 402
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Book Description
Author: Ralph J. Haefner
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 136
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Book Description
Author: North American Lake Management Society. Conference
Publisher:
ISBN:
Category : Lake restoration
Languages : en
Pages : 628
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Book Description
Author: United States. Congress. House. Committee on Science and Technology. Subcommittee on Energy Development and Applications
Publisher:
ISBN:
Category : Acid rain
Languages : en
Pages : 1300
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Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 1074
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Book Description
Author: United States. Environmental Protection Agency
Publisher:
ISBN:
Category :
Languages : en
Pages : 1760
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Book Description
Author: Hossein Riazoshams
Publisher: John Wiley & Sons
ISBN: 1119010454
Category : Mathematics
Languages : en
Pages : 261
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Book Description
The first book to discuss robust aspects of nonlinear regression—with applications using R software Robust Nonlinear Regression: with Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the classic and robust aspects of nonlinear regression and focuses on outlier effects. It develops new methods in robust nonlinear regression and implements a set of objects and functions in S-language under SPLUS and R software. The software covers a wide range of robust nonlinear fitting and inferences, and is designed to provide facilities for computer users to define their own nonlinear models as an object, and fit models using classic and robust methods as well as detect outliers. The implemented objects and functions can be applied by practitioners as well as researchers. The book offers comprehensive coverage of the subject in 9 chapters: Theories of Nonlinear Regression and Inference; Introduction to R; Optimization; Theories of Robust Nonlinear Methods; Robust and Classical Nonlinear Regression with Autocorrelated and Heteroscedastic errors; Outlier Detection; R Packages in Nonlinear Regression; A New R Package in Robust Nonlinear Regression; and Object Sets. The first comprehensive coverage of this field covers a variety of both theoretical and applied topics surrounding robust nonlinear regression Addresses some commonly mishandled aspects of modeling R packages for both classical and robust nonlinear regression are presented in detail in the book and on an accompanying website Robust Nonlinear Regression: with Applications using R is an ideal text for statisticians, biostatisticians, and statistical consultants, as well as advanced level students of statistics.
