Suppr超能文献

广义线性模型中的分类图像和气泡图像。

Classification images and bubbles images in the generalized linear model.

作者信息

Murray Richard F

机构信息

Department of Psychology and Centre for Vision Research, York University, Toronto, ON, Canada.

出版信息

J Vis. 2012 Jul 9;12(7):2. doi: 10.1167/12.7.2.

Abstract

Classification images and bubbles images are psychophysical tools that use stimulus noise to investigate what features people use to make perceptual decisions. Previous work has shown that classification images can be estimated using the generalized linear model (GLM), and here I show that this is true for bubbles images as well. Expressing the two approaches in terms of a single statistical model clarifies their relationship to one another, makes it possible to measure classification images and bubbles images simultaneously, and allows improvements developed for one method to be used with the other.

摘要

分类图像和气泡图像是心理物理学工具,它们利用刺激噪声来研究人们用于做出感知决策的特征。先前的研究表明,可以使用广义线性模型(GLM)来估计分类图像,在此我表明气泡图像也是如此。用单一统计模型来表述这两种方法,阐明了它们彼此之间的关系,使得同时测量分类图像和气泡图像成为可能,并允许将为一种方法开发的改进应用于另一种方法。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验