Beyond the expectation–maximization (EM) algorithm for vector parameters, the EM for an unknown distribution function is often used in mixture models, density estimation, and signal recovery problems. We prove the convergence of the EM in functional spaces and show the EM likelihoods in this...

In this article, we study the power properties of quadratic-distance-based goodness-of-fit tests. First, we introduce the concept of a <italic>root kernel</italic> and discuss the considerations that enter the selection of this kernel. We derive an easy to use normal approximation to the power of quadratic...

We propose a general class of risk measures which can be used for data-based evaluation of parametric models. The loss function is defined as the generalized quadratic distance between the true density and the model proposed. These distances are characterized by a simple quadratic form structure...

We develop a new method for building a hierarchical tree from binary sequence data. It is based on an ancestral mixture model. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By varying the sieve parameter, one can create a hierarchical tree...