000			02834nam a2200325| 4500
001			83982
005			20220110131126.0
010			_a978-1-4614-4475-6 _dcompra
090			_a83982
100			_a20190128d2012 k||y0pory50 ba
101			_aeng
102			_aUS
200			_aModeling psychophysical data in R _bDocumento eletrn̤ico _fKenneth Knoblauch, Laurence T. Maloney
210			_aNew York, NY _cSpringer _d2012
215			_aXV, 365 p. _cil.
225			_aUse R! _h32
300			_aColocaȯ̂: Online
303			_aMany of the commonly used methods for modeling and fitting psychophysical data are special cases of statistical procedures of great power and generality, notably the Generalized Linear Model (GLM). This book illustrates how to fit data from a variety of psychophysical paradigms using modern statistical methods and the statistical language R. The paradigms include signal detection theory, psychometric function fitting, classification images and more. In two chapters, recently developed methods for scaling appearance, maximum likelihood difference scaling and maximum likelihood conjoint measurement are examined. The authors also consider the application of mixed-effects models to psychophysical data. R is an open-source  programming language that is widely used by statisticians and is seeing enormous growth in its application to data in all fields. It is interactive, containing many powerful facilities for optimization, model evaluation, model selection, and graphical display of data. The reader who fits data in R can readily make use of these methods. The researcher who uses R to fit and model his data has access to most recently developed statistical methods. This book does not assume that the reader is familiar with R, and a little experience with any programming language is all that is needed to appreciate this book. There are large numbers of examples of R in the text and the source code for all examples is available in an R package MPDiR available through R. Kenneth Knoblauch is a researcher in the Department of Integrative Neurosciences in Inserm Unit 846, The Stem Cell and Brain Research Institute and associated with the University Claude Bernard, Lyon 1, in France.  Laurence T. Maloney is Professor of Psychology and Neural Science at New York University. His research focusses on applications of mathematical models to perception, motor control and decision making.
410			_x2197-5736 _v32
606			_91379 _aEstats̕tica matemt̀ica
606			_93627 _aEstats̕tica
680			_aQA276
700			_933430 _aKnoblauch _bKenneth
701			_933431 _aMaloney _bLaurence T. _4070
801			_gRPC _aPT
856			_uhttps://doi.org/10.1007/978-1-4614-4475-6
942			_2lcc _cF _n0