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  Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data

Schütt, H. H., Harmeling, S., Macke, J. H., & Wichmann, F. A. (2016). Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research, 122, 105-123.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-2903-B Version Permalink: https://hdl.handle.net/21.11116/0000-0005-D996-D
Genre: Journal Article

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Schütt_Painfree.pdf (Publisher version), 2MB
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http://www.ncbi.nlm.nih.gov/pubmed/27013261 (Publisher version)
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 Creators:
Schütt, Heiko H., Author
Harmeling, Stefan, Author
Macke, Jakob H.1, Author           
Wichmann, Felix A., Author
Affiliations:
1Max Planck Research Group Neural Systems Analysis, Center of Advanced European Studies and Research (caesar), Max Planck Society, ou_2173683              

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 Dates: 2016-03-24
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: eDoc: doi: 10.1016/j.visres.2016.02.002
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Title: Vision Research
  Other : Vision Res.
Source Genre: Journal
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Publ. Info: Amsterdam : Pergamon
Pages: - Volume / Issue: 122 Sequence Number: - Start / End Page: 105 - 123 Identifier: ISSN: 0042-6989
CoNE: https://pure.mpg.de/cone/journals/resource/954925451842