Contributions within Discipline: The findings have improved the efficiency of adaptive measurement in psychophysics, in experimental paradigms where individual trials are often information-poor and experiments are consequently long. The Bayesian adaptive methodology improves the information throughput in such experiments and improves on heuristic methods. The multivariate estimation also extends the utility of Bayesian adaptive estimation into realms where it is even more important because of the \u27curse of dimensionality\u27 (where the size of parameter space is exponential in the number of parameters). In addition, the work on nonparametric adaptive methods has helped reveal the source of bias in simpler adaptive methodology that has of...
Monte Carlo simulaition was used to investigate score bias'and information characteristics of O...
Research on human motor adaptation has often focused on how people adapt to self-generated or extern...
There are many statistics which can be used to characterize data sets and provide valuable informati...
A psychometric function can be described by its shape and four parameters: position or threshold, sl...
Simulation studies have shown how Bayesian adaptive estimation methods should be set up for optimal ...
Bayesian adaptive methods have been extensively used in psychophysics to estimate the point at which...
A new Bayesian adaptive psychometric method based on the theory of optimal experiments is introduced...
In experiments to estimate parameters of a parametric model, Bayesian experiment design allows measu...
AbstractWe introduce a new Bayesian adaptive method for acquisition of both threshold and slope of t...
This paper investigates the theoretical bound to reduce the parameter uncertainty in Bayesian adapti...
An adaptive psychometric procedure that places each trial at the current most probable Baye& ian...
Most psychological experiments measure human cognitive function through the response time and accura...
The adaptive experimentation methodology has been adopted in visual psychophysical modeling in the p...
Abstract An ideal experiment is one in which data collection is efficient and the results are maxima...
Monte carlo simulation was used to investigate score bias and information characteristics of Owen’s...
Monte Carlo simulaition was used to investigate score bias'and information characteristics of O...
Research on human motor adaptation has often focused on how people adapt to self-generated or extern...
There are many statistics which can be used to characterize data sets and provide valuable informati...
A psychometric function can be described by its shape and four parameters: position or threshold, sl...
Simulation studies have shown how Bayesian adaptive estimation methods should be set up for optimal ...
Bayesian adaptive methods have been extensively used in psychophysics to estimate the point at which...
A new Bayesian adaptive psychometric method based on the theory of optimal experiments is introduced...
In experiments to estimate parameters of a parametric model, Bayesian experiment design allows measu...
AbstractWe introduce a new Bayesian adaptive method for acquisition of both threshold and slope of t...
This paper investigates the theoretical bound to reduce the parameter uncertainty in Bayesian adapti...
An adaptive psychometric procedure that places each trial at the current most probable Baye& ian...
Most psychological experiments measure human cognitive function through the response time and accura...
The adaptive experimentation methodology has been adopted in visual psychophysical modeling in the p...
Abstract An ideal experiment is one in which data collection is efficient and the results are maxima...
Monte carlo simulation was used to investigate score bias and information characteristics of Owen’s...
Monte Carlo simulaition was used to investigate score bias'and information characteristics of O...
Research on human motor adaptation has often focused on how people adapt to self-generated or extern...
There are many statistics which can be used to characterize data sets and provide valuable informati...