Purpose: To understand how users of online marketplaces process market signals in their decision making and whether this depends on if the good is of high or low involvement. Design/methodology/approach: The paper employs a mixed methods approach. Study 1 draws on an analysis of interviews with...

We consider estimating the variance of a general U-statistic when it is used as an unbiased estimator of the parameter of interesttheta=E(K) where K is the kernel function. Long established results demonstrate the asymptotic normality of U-statistics and their asymptotic variance under...

Multivariate mixture models provide a convenient method of densityestimation and model based clustering as well as providing possible explanations for the actual data generationprocess. But the problem of choosing the number of components ($g$) in a statistically meaningful way is still asubject...

Mixture models have been popular in the literature of both statistics and social science. In this dissertation, we propose a new mixture model, namely, nonparametric finite mixture of regression models, which can be viewed as a natural extension of finite mixture of linear regression. In the...

An almost nonparametric approach for the estimation of the mixing proportion in a mixture of two distributions, when we have a vector of observations on each subject, is to define a mixture of binomials. A mixture of binomials can be obtained if the vector of observations is mapped into a vector...

Parameter identifiability is very useful if one wishes to make inferences in a statistical model. There are two important nonidentifiabilities in finite mixture models : boundary nonidentifiability and label nonidentifiability. Although parameters are not identifiable in the strict sense, in...