Appletree: A multinomial processing tree modeling program for macintosh computers
Appletree: A multinomial processing tree modeling program for macintosh computers
复制标题
Appletree：用于 Macintosh 计算机的多项处理树建模程序
DOI：
10.3758/bf03200748
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
R. Rothkegel
中科院分区：
文献类型：
--
作者：
R. Rothkegel
多项处理树（MPT）模型是一种统计模型，允许通过不可观察（认知）状态集预测分类频率数据。在MPT模型中，事件属于某个类别的概率是状态概率的乘积之和。AppleTree是一个用于Macintosh的计算机程序，用于测试用户定义的MPT模型。它可以将模型参数拟合到经验频率数据，为参数提供置信区间，为模型生成树图，并执行可识别性检查。在这篇文章中，AppleTree使用的算法和程序的处理进行了描述。
Multinomial processing tree (MPT) models are statistical models that allow for the prediction of categorical frequency data by sets of unobservable (cognitive) states. In MPT models, the probability that an event belongs to a certain category is a sum of products of state probabilities. AppleTree is a computer program for Macintosh for testing user-defined MPT models. It can fit model parameters to empirical frequency data, provide confidence intervals for the parameters, generate tree graphs for the models, and perform identifiability checks. In this article, the algorithms used by AppleTree and the handling of the program are described.