Uemura [1] discovered the mapping formula for Type 1 Vague events and presented an alternative problem as example of its application. Since it is well known that leads to sequential Bayesian inference, flow subsequent research was make multidimensional, introduce concept time, derive a Markov (decision) process. Furthermore, we formulated stochastic differential equations them [2]. This paper r...

Article history: Received 10 November 2011 Revised 19 September 2012 Accepted 24 September 2012 Available online 4 October 2012 Communicated by Stephen D. Cohen

In this paper, we focus on single-index models for longitudinal data. We propose a procedure to estimate the single-index component and the unknown link function based on the combination of the penalized splines and quadratic inference functions. It is shown that the proposed estimation method has good asymptotic properties. We also evaluate the finite sample performance of the proposed method ...

Linear chains and trees are basic building blocks in many applications of graphical models, and they admit simple exact maximum a-posteriori (MAP) inference algorithms based on message passing. However, in many cases this computation is prohibitively expensive, due to quadratic dependence on variables’ domain sizes. The standard algorithms are inefficient because they compute scores for hypothe...

This paper analyzes energy equipartition in linear Hamiltonian systems in a deterministic setting.We consider the group of phase space symmetries of a stable linear Hamiltonian system, and characterize the subgroup of symmetries whose elements preserve the time averages of quadratic functions along the trajectories of the system. As a corollary, we show that if the system has simple eigenvalues...

Correlation structure contains important information about longitudinal data. Existing sufficient dimension reduction approaches assuming independence may lead to substantial loss of efficiency. We apply the quadratic inference function to incorporate the correlation information and apply the transformation method to recover the central subspace. The proposed estimators are shown to be consiste...

Maximum likelihood (ML) for phylogenetic inference from sequence data remains a method of choice, but has computational limitations. In particular, it cannot be applied for a global search through all potential trees when the number of taxa is large, and hence a heuristic restriction in the search space is required. In this paper, we derive a quadratic approximation, QAML, to the likelihood fun...