Likelihood-Free Methods for Cognitive Science

This book explains the foundation of approximate Bayesian computation (ABC), an approach to Bayesian inference that does not require the specification of a likelihood function. As a result, ABC can be used to estimate posterior distributions of parameters for simulation-based models. Simulation-base...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Palestro, James J. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Sederberg, Per B. (http://id.loc.gov/vocabulary/relators/aut), Osth, Adam F. (http://id.loc.gov/vocabulary/relators/aut), Van Zandt, Trisha (http://id.loc.gov/vocabulary/relators/aut), Turner, Brandon M. (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Σειρά:Computational Approaches to Cognition and Perception,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03391nam a2200505 4500
001 978-3-319-72425-6
003 DE-He213
005 20191028072549.0
007 cr nn 008mamaa
008 180207s2018 gw | s |||| 0|eng d
020 |a 9783319724256  |9 978-3-319-72425-6 
024 7 |a 10.1007/978-3-319-72425-6  |2 doi 
040 |d GrThAP 
050 4 |a BF201 
072 7 |a JMR  |2 bicssc 
072 7 |a PSY008000  |2 bisacsh 
072 7 |a JMR  |2 thema 
082 0 4 |a 153  |2 23 
100 1 |a Palestro, James J.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Likelihood-Free Methods for Cognitive Science  |h [electronic resource] /  |c by James J. Palestro, Per B. Sederberg, Adam F. Osth, Trisha Van Zandt, Brandon M. Turner. 
250 |a 1st ed. 2018. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2018. 
300 |a XIV, 129 p. 27 illus., 7 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Computational Approaches to Cognition and Perception,  |x 2510-1889  
505 0 |a Chapter 1. Motivation -- Chapter 2. Likelihood-Free Algorithms -- Chapter 3. A Tutorial -- Chapter 4. Validations -- Chapter 5. Applications -- Chapter 6. Conclusions -- Chapter 7. Distributions. 
520 |a This book explains the foundation of approximate Bayesian computation (ABC), an approach to Bayesian inference that does not require the specification of a likelihood function. As a result, ABC can be used to estimate posterior distributions of parameters for simulation-based models. Simulation-based models are now very popular in cognitive science, as are Bayesian methods for performing parameter inference. As such, the recent developments of likelihood-free techniques are an important advancement for the field. Chapters discuss the philosophy of Bayesian inference as well as provide several algorithms for performing ABC. Chapters also apply some of the algorithms in a tutorial fashion, with one specific application to the Minerva 2 model. In addition, the book discusses several applications of ABC methodology to recent problems in cognitive science. Likelihood-Free Methods for Cognitive Science will be of interest to researchers and graduate students working in experimental, applied, and cognitive science. . 
650 0 |a Cognitive psychology. 
650 1 4 |a Cognitive Psychology.  |0 http://scigraph.springernature.com/things/product-market-codes/Y20060 
700 1 |a Sederberg, Per B.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Osth, Adam F.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Van Zandt, Trisha.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Turner, Brandon M.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319724249 
776 0 8 |i Printed edition:  |z 9783319724263 
776 0 8 |i Printed edition:  |z 9783319891811 
830 0 |a Computational Approaches to Cognition and Perception,  |x 2510-1889  
856 4 0 |u https://doi.org/10.1007/978-3-319-72425-6  |z Full Text via HEAL-Link 
912 |a ZDB-2-BSP 
950 |a Behavioral Science and Psychology (Springer-41168)