000			03541nam a22005175i 4500
001			978-0-387-09616-2
003			DE-He213
005			20250710083924.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387096162 _a99780387096162
024	7		_a10.1007/978-0-387-09616-2 _2doi
082	0	4	_a519.5 _223
100	1		_aRitz, Christian. _eeditor.
245	1	0	_aNonlinear Regression with R _h[recurso electrónico] / _cedited by Christian Ritz, Jens Carl Streibig.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_aXII, 148p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aUse R
505	0		_aGetting Started -- Starting Values and Self-starters -- More on nls() -- Model Diagnostics -- Remedies for Model Violations -- Uncertainty, Hypothesis Testing, and Model Selection -- Grouped Data.
520			_aR is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. Currently, R offers a wide range of functionality for nonlinear regression analysis, but the relevant functions, packages and documentation are scattered across the R environment. This book provides a coherent and unified treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology. The book begins with an introduction on how to fit nonlinear regression models in R. Subsequent chapters explain in more depth the salient features of the fitting function nls(), the use of model diagnostics, the remedies for various model departures, and how to do hypothesis testing. In the final chapter grouped-data structures, including an example of a nonlinear mixed-effects regression model, are considered. Christian Ritz has a PhD in biostatistics from the Royal Veterinary and Agricultural University. For the last 5 years he has been working extensively with various applications of nonlinear regression in the life sciences and related disciplines, authoring several R packages and papers on this topic. He is currently doing postdoctoral research at the University of Copenhagen. Jens C. Streibig is a professor in Weed Science at the University of Copenhagen. He has for more than 25 years worked on selectivity of herbicides and more recently on the ecotoxicology of pesticides and has extensive experience in applying nonlinear regression models. Together with the first author he has developed short courses on the subject of this book for students in the life sciences.
650		0	_aSTATISTICS.
650		0	_aTOXICOLOGY.
650		0	_aEPIDEMIOLOGY.
650		0	_aFORESTS AND FORESTRY.
650		0	_aMATHEMATICAL STATISTICS.
650		0	_aENGINEERING.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICAL THEORY AND METHODS.
650	2	4	_aPHARMACOLOGY/TOXICOLOGY.
650	2	4	_aCOMPUTATIONAL INTELLIGENCE.
650	2	4	_aEPIDEMIOLOGY.
650	2	4	_aFORESTRY.
700	1		_aStreibig, Jens Carl. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387096155
830		0	_aUse R
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-09616-2 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c55992 _d55992