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We describe a Bayesian method based on Markov chain simulation to study the phylogenetic relationship in a group of DNA sequences. Under simple models of mutational events, our method produces a Markov chain whose stationary distribution is the conditional distribution of the phylogeny given the observed sequences. Our algorithm strikes a reasonable balance… (More)

- Deborah L. Burr, Hani Doss
- 2004

In meta-analysis there is an increasing trend to explicitly acknowledge the presence of study variability through random effects models. That is, one assumes that for each study, there is a study-specific effect and one is observing an estimate of this latent variable. In a random effects model, one assumes that these study-specific effects come from some… (More)

- Yufeng Liu, Xiaotong Shen, Hani Doss
- 2005

Many margin-based binary classification techniques such as support vector machine (SVM) andψ-learning deliver high performance. An earlier article proposed a new multicategory ψ-learning methodology that shows great promise in generalization ability. However, ψ-learning is computationally difficult because it requires handling a nonconvex minimization… (More)

- Matteo Cesari, Bruno Vellas, +8 authors Marco Pahor
- The journals of gerontology. Series A, Biological…
- 2015

BACKGROUND
The frailty syndrome is as a well-established condition of risk for disability. Aim of the study is to explore whether a physical activity (PA) intervention can reduce prevalence and severity of frailty in a community-dwelling elders at risk of disability.
METHODS
Exploratory analyses from the Lifestyle Interventions and Independence for Elders… (More)

The Markov chain simulation method has been successfully used in many problems, including some that arise in Bayesian statistics. We give a self-contained proof of the convergence of this method in general state spaces under conditions that are easy to verify.

- Hani Doss
- 2009

We consider situations in Bayesian analysis where the prior is indexed by a hyperparameter taking on a continuum of values. We distinguish some arbitrary value of the hyperparameter, and consider the problem of estimating the Bayes factor for the model indexed by the hyperparameter vs. the model specified by the distinguished point, as the hyperparameter… (More)

- Deborah L. Burr, Hani Doss, Glen E. Cooke, Pascal J. Goldschmidt-Clermont
- Statistics in medicine
- 2003

The Pl(A2) polymorphism of the glycoprotein IIIa subunit of the fibrinogen receptor (GPIIb-IIIa) has been reported by some studies to be associated with an increased risk of coronary thrombosis. Following the first paper on the subject in 1996, a large number of studies have investigated the relationship between this polymorphism and coronary thrombosis,… (More)

We consider situations in Bayesian analysis where we have a family of priors νh on the parameter θ, where h varies continuously over a space H, and we deal with two related problems. The first involves sensitivity analysis and is stated as follows. Suppose we fix a function f of θ. How do we efficiently estimate the posterior expectation of f(θ)… (More)

- Hani Doss, Fred W. Huffer
- 1998

Consider the model in which the data consist of possibly censored lifetimes, and one puts a mixture of Dirichlet process priors on the common survival distribution. The exact computation of the posterior distribution of the survival function is in general impossible to obtain. This paper develops and compares the performance of several simulation… (More)

- Judith Schwartzbaum, Anders Ahlbom, +6 authors Maria Feychting
- Cancer research
- 2005

A reduced risk of primary malignant adult brain tumors is observed among people reporting asthma, hay fever, and other allergic conditions; however, findings may be attributed to prediagnostic effects of tumors or recall bias. To determine whether asthma and allergic condition polymorphisms are inversely related to glioblastoma multiforme (GBM) risk, we… (More)