使用ML - PEST对感觉阈值进行有效估计。
Efficient estimation of sensory thresholds with ML-PEST.
作者信息
Harvey L O
机构信息
Department of Psychology, University of Colorado, Boulder 80309-0345, USA.
出版信息
Spat Vis. 1997;11(1):121-8. doi: 10.1163/156856897x00159.
PMID:9304762
Abstract
A set of C and C+2 routines are described that allow the efficient estimation of sensory thresholds in psychophysical experiments using a maximum-likelihood staircase procedure. They have been used effectively in visual, auditory, gustatory, and olfactory psychophysics.
摘要
本文描述了一组C语言和C + 2语言的程序，这些程序能够使用最大似然阶梯法在心理物理学实验中有效地估计感觉阈值。它们已在视觉、听觉、味觉和嗅觉心理物理学中得到有效应用。
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