We develop Mean Field Variational Bayes methodology for fast approximate inference in Bayesian Generalized Extreme Value additive model analysis. Such models are useful for flexibly assessing the impact of continuous ...
A semiparametric version of the generalized linear model for regression response was developed by replacing the linear combination with nonparametric components. The generalized partially linear single-index models were ...
We develop a family of distributions which allow for over- and underdispersion relative to the Poisson. This latter feature is particularly appealing since many existing methods only allow for overdispersion. These ...
In stock market or other financial market systems, the technical trading rules are used widely to generate buy and sell alert signals. In each rule, there are many parameters. The users often want to get the best signal ...
The Pro/Pro polymorphism of p53 codon 72 has been reported to be related to bladder and lung cancer, but its relationship with skin cancer is unclear. We assessed the hypothesis that there is a relationship between the p53 ...
Abstract: Analytical or coding errors in posterior simulators can produce reasonable but incorrect approximations of posterior moments. This article develops simple tests of posterior simulators that detect both kinds of ...
A firms growth and failure are the two sides of the same coin. This paper reports new phenomenological findings for firm size distribution and growth, and bankruptcy. This paper is based on [Y. Fujiwara et al., Physica A ...
This paper deals with the well-posedness of the global solution of a small initial value problem for a generalized Boussinesq equation. The conditions for the existence and uniqueness of the solution to the problem are ...
The applied statistician often encounters the need to compare two or more groups with respect to more than one outcome or response. Several options are generally available, including reducing the dimension of the problem ...
Real-world phenomena are frequently modelled by Bayesian hierarchical models. The building-blocks in such models are the distribution of each variable conditional on parent and/or neighbour variables in the graph. The ...
For a graph of m nodes and n edges, an algorithm for testing the isomorphism of graphs is given. The complexity of the algorithm is a maximum of O(mn(2)) in almost all cases, with a considerable reduction if sparsity is ...
Monte Carlo simulation of weak approximation of stochastic differential equations constitutes an intensive computational task. In applications such as finance, for instance, to achieve "real time" execution, as often ...