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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. (2016). Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research, 122, 105-123. doi:10.1016/j.visres.2016.02.002.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-267B-5 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-40A2-C
Genre: Journal Article

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 Creators:
Schütt, Heiko H.1, Author
Harmeling, Stefan1, Author
Macke, Jakob H.1, Author
Wichmann, FA2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
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Language(s): eng - English
 Dates: 2016-05
 Publication Status: Issued
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 Rev. Type: -
 Identifiers: DOI: 10.1016/j.visres.2016.02.002
BibTex Citekey: Schütt2016105
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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