ABSTRACT
In psychology, the recognition that the complete distribution function of reaction times (RTs) may contain critical information about the underlying stochastic mechanism not accessible by only considering their mean, has led to the development of many RT models predicting specific distribution functions. The specification of a distribution through its quantile function takes away the need to describe a distribution through its moments. Alternative measures in terms of quantiles are available, e.g., the median as a measure of location. The quantile spread of a distribution describes how the probability mass is placed symmetrically about its median and hence can be used to formalize concepts such as peakedness and tail weight traditionally associated with kurtosis. The density for the Beta distribution, frequently used in modeling. An alternative distribution is the Kumaraswamy distribution, which is, in many respects, very similar to the Beta distribution. In contrast to the Beta distribution, Kumaraswamy distribution has no closed-form expressions for the mean and variance.
