scholarly journals Hallucinations and perceptual inference

2005 ◽  
Vol 28 (6) ◽  
pp. 764-766 ◽  
Author(s):  
Karl J. Friston
Keyword(s):  
Attention Deficit ◽  
Bayesian Models ◽  
Subjective Perception ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models ◽  
Perceptual Inference ◽  
Cholinergic Systems ◽  
Neuronal Mechanisms ◽  
Constructive Models

This commentary takes a closer look at how “constructive models of subjective perception,” referred to by Collerton et al. (sect. 2), might contribute to the Perception and Attention Deficit (PAD) model. It focuses on the neuronal mechanisms that could mediate hallucinations, or false inference – in particular, the role of cholinergic systems in encoding uncertainty in the context of hierarchical Bayesian models of perceptual inference (Friston 2002b; Yu & Dayan 2002).

scholarly journals Hierarchical Bayesian models for soil CO2flux using soil texture: a case study in central Hokkaido, Japan

2014 ◽  
Vol 61 (1) ◽  
pp. 116-132 ◽  
Author(s):  
Xi Li ◽  
Kiwamu Ishikura ◽  
Chunying Wang ◽  
Jagadeesh Yeluripati ◽  
Ryusuke Hatano
Keyword(s):  
Soil Texture ◽  
Bayesian Models ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models

Analysis of High-Throughput Electrochemical Impedance Spectroscopy via Hierarchical Bayesian Models

2021 ◽  
Vol MA2021-02 (44) ◽  
pp. 1353-1353
Author(s):  
Jake Huang ◽  
Meagan Papac ◽  
Andriy Zakutayev ◽  
Ryan O'Hayre
Keyword(s):  
Electrochemical Impedance Spectroscopy ◽  
Impedance Spectroscopy ◽  
High Throughput ◽  
Electrochemical Impedance ◽  
Bayesian Models ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models

scholarly journals Should we be concerned about multiple comparisons in hierarchical Bayesian models?

2019 ◽  
Vol 10 (4) ◽  
pp. 553-564 ◽  
Author(s):  
Kiona Ogle ◽  
Drew Peltier ◽  
Michael Fell ◽  
Jessica Guo ◽  
Heather Kropp ◽  
...  
Keyword(s):  
Bayesian Models ◽  
Multiple Comparisons ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models

Examining driver injury severity in intersection-related crashes using cluster analysis and hierarchical Bayesian models

2018 ◽  
Vol 120 ◽  
pp. 139-151 ◽  
Author(s):  
Zhenning Li ◽  
Cong Chen ◽  
Yusheng Ci ◽  
Guohui Zhang ◽  
Qiong Wu ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Injury Severity ◽  
Bayesian Models ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models

Hierarchical Bayesian Models

2015 ◽  
Author(s):  
N. Thompson Hobbs ◽  
Mevin B. Hooten
Keyword(s):  
Bayesian Networks ◽  
Hierarchical Models ◽  
Bayesian Models ◽  
Research Problem ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models ◽  
Broad Application ◽  
Joint Distributions ◽  
Definition Of

This chapter seeks to explain hierarchical models and how they differ from simple Bayesian models and to illustrate building hierarchical models using mathematically correct expressions. It begins with the definition of hierarchical models. Next, the chapter introduces four general classes of hierarchical models that have broad application in ecology. These classes can be used individually or in combination to attack virtually any research problem. Examples are used to show how to draw Bayesian networks that portray stochastic relationships between observed and unobserved quantities. The chapter furthermore shows how to use network drawings as a guide for writing posterior and joint distributions.

Comparing two multinomial samples using hierarchical Bayesian models

2019 ◽  
Vol 9 (2) ◽  
pp. 145-154
Author(s):  
A. R. Masegosa ◽  
A. Torres ◽  
M. Morales ◽  
A. Salmerón
Keyword(s):  
Bayesian Models ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models
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