Fitting wald and ex-Wald distributions to response time data: an example using functions for the S-PLUS package.

Andrew Heathcote
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引用次数: 88

Abstract

Schwarz (2001, 2002) proposed the ex-Wald distribution, obtained from the convolution of Wald and exponential random variables, as a model of simple and go/no-go response time. This article provides functions for the S-PLUS package that produce maximum likelihood estimates of the parameters for the ex-Wald, as well as for the shifted Wald and ex-Gaussian, distributions. In a Monte Carlo study, the efficiency and bias of parameter estimates were examined. Results indicated that samples of at least 400 are necessary to obtain adequate estimates of the ex-Wald and that, for some parameter ranges, much larger samples may be required. For shifted Wald estimation, smaller samples of around 100 were adequate, at least when fits identified by the software as having ill-conditioned maximums were excluded. The use of all functions is illustrated using data from Schwarz (2001). The S-PLUS functions and Schwarz's data may be downloaded from the Psychonomic Society's Web archive, www. psychonomic.org/archive/.

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拟合wald和ex-Wald分布到响应时间数据:使用S-PLUS包函数的示例。
Schwarz(2001,2002)提出了由Wald和指数随机变量卷积得到的ex-Wald分布作为简单和go/no-go响应时间的模型。本文提供了S-PLUS包的函数,这些函数产生了前瓦尔德分布、移位瓦尔德分布和前高斯分布的参数的最大似然估计。在蒙特卡罗研究中,检验了参数估计的效率和偏差。结果表明,至少需要400个样本才能获得足够的前瓦尔德估计,并且对于某些参数范围,可能需要更大的样本。对于移位Wald估计,大约100个较小的样本就足够了,至少当软件识别出具有病态最大值的拟合被排除时。使用施瓦茨(2001)的数据说明了所有函数的使用。S-PLUS的功能和施瓦茨的数据可以从心理学会的网站下载。psychonomic.org/archive/。
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