Semiparametric Bayesian approaches to systems factorial technology

DOI10.1016/j.jmp.2016.02.008zbMath1396.62265OpenAlexW2320578065MaRDI QIDQ730154

Steven N. MacEachern, Trisha Van Zandt, James T. Townsend, Joseph W. Houpt, Mario Peruggia

Publication date: 23 December 2016

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmp.2016.02.008

zbMATH Keywords

capacityhazard ratespiecewise exponentialreaction timessurvivor function

Mathematics Subject Classification ID

Bayesian inference (62F15) Psychophysics and psychophysiology; perception (91E30) Applications of statistics to psychology (62P15)

Related Items (5)

Systems factorial technology analysis of mixtures of processing architectures ⋮ Parametric supplements to systems factorial analysis: identifying interactive parallel processing using systems of accumulators ⋮ Hierarchical Bayesian mixture models of processing architectures and stopping rules ⋮ Adaptive design for systems factorial technology experiments ⋮ A hierarchical Bayesian approach to distinguishing serial and parallel processing

Uses Software

• Stan

Cites Work

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