Dynamic Display of Changing Posterior in Bayesian Survival Analysis: The Software

We consider the problem of estimating an unknown distribution function in the presence of censoring under the conditions that a parametric model is believed to hold approximately. We use a Bayesian approach, in which the prior on is a mixture of Dirichlet distributions. A hyperparameter of the prior determines the extent to which this prior concentrates its mass around the parametric family. A Gibbs sampling algorithm to estimate the posterior distributions of the parameters of interest is reviewed. An importance sampling scheme enables us to use the output of the Gibbs sampler to very quickly recalculate the posterior when we change the hyperparameters of the prior. The calculations can be done sufficiently fast to enable the dynamic display of the changing posterior as the prior hyperparameters are varied. This paper provides a literate program completely documenting the code for performing the dynamic graphics.

Elliptic, Parabolic and Hyperbolic Analytic Function Theory--0: Geometry of Domains

This paper lays down a foundation for a systematic treatment of three main (elliptic, parabolic and hyperbolic) types of analytic function theory based on the representation theory of SL(2,R) group. We describe here geometries of corresponding domains. The principal role is played by Clifford algebras of matching types. Keywords: analytic function theory, semisimple groups, elliptic, parabolic, hyperbolic, Clifford algebrasComment: 14 pages, AMS-LaTeX, 31 PS graphcs in 7 Figures; v2--the missing PS file is included now; v3 minor corrections, reference added; v4 numerous misprints correcte

An Example of Clifford Algebras Calculations with GiNaC

This example of Clifford algebras calculations uses GiNaC (http://www.ginac.de/) library, which includes a support for generic Clifford algebra starting from version~1.3.0. Both symbolic and numeric calculation are possible and can be blended with other functions of GiNaC. This calculations was made for the paper math.CV/0410399. Described features of GiNaC are already available at PyGiNaC (http://sourceforge.net/projects/pyginac/) and due to course should propagate into other software like GNU Octave (http://www.octave.org/), gTybalt (http://www.fis.unipr.it/~stefanw/gtybalt.html), which use GiNaC library as their back-end.Comment: 20 pages, LaTeX2e, 12 PS graphics in one figure; v3 code improvements; v4 small code correction for new libraries; v5 comments are redesined to be more readabl

Analytical strategies in imaging genetics : assessment of potential risk factors for neurodevelopmental domains

Imaging Genetics (IG) aims to test how genetic information influences brain structure and function, cognitive processes and complex neurodevelopmental domains, combining magnetic resonance imaging-based brain features and genetic data from the same individual. IG studies represent an opportunity to deepen our knowledge of the biological mechanisms of neurodevelopmental domains and complex brain disorders. Most studies focus on individual correlation and association tests between a subset of genetic variants (usually single nucleotide polymorphisms, SNPs) and a single measurement of the brain. Despite the great success of univariate approaches, given the current focus of imaging genetic studies in which genome-wide, whole-brain studies should be analyzed, the development of novel statistical methods becomes crucial. The main aim of this thesis consists of investigating genetic determinants of structural brain change, which in turn affect neurodevelopmental domains. We propose the application and development of statistical strategies to improve the assessment of significant relationships associated with neurodevelopmental domains. Specifically, we focus our research efforts on understanding what genomic changes in the cerebral structure allow improvements in the assessment of risk factors associated with Attention-Deficit/Hyperactivity disorder domains, and related cognitive processes such as attention function.Els estudis que combinen la informació genètica i de neuroimatge (IG) pretenen provar com la informació genètica influeix en l'estructura i funció cerebral, en el comportament, i en els dominis del neurodesenvolupament, combinant la informació extreta de ressonàncies magnètiques del cervell i de la informació genètica d'un mateix individu. Els estudis d'IG representen una oportunitat per aprofundir en el coneixement dels mecanismes biològics dels dominis del desenvolupament neurològic. La majoria dels estudis es centren en la correlació individual i en proves d'associació entre un subconjunt de variants genètiques (en general polimorfismes d'un únic nucleòtid, SNPs) i una única mesura d'una regió cerebral. Però, malgrat el gran èxit en l'enfocament univariat, donades les perspectives actuals dels estudis d'IG, en els quals es pretenen analitzar les relacions cerebrals de tot el genoma envers tota la informació del cervell, el desenvolupament de nous mètodes estadístics específics esdevé crucial. L'objectiu principal d'aquesta tesi consisteix a investigar els determinants genètics relacionats amb els canvis estructurals del cervell, que a la vegada, afecten els dominis del neurodesenvolupament. Proposem l'aplicació i el desenvolupament d'estratègies estadístiques per millorar l’avaluació de les relacions biològiques associades als dominis del neurodesenvolupament. Específicament, centrem els nostres esforços de recerca en comprendre quins canvis genètics que influeixen l'estructura cerebral permeten millorar l'avaluació dels factors de risc associats als dominis del trastorn per dèficit d'atenció i hiperactivitat, i a processos cognitius relacionats, com la funció d'atenció

SASWeave: Literate Programming Using SAS

SASweave is a collection of scripts that allow one to embed SAS code into a LATEX document, and automatically incorporate the results as well. SASweave is patterned after Sweave, which does the same thing for code written in R. In fact, a document may contain both SAS and R code. Besides the convenience of being able to easily incorporate SAS examples in a document, SASweave facilitates the concept of "literate programming": having code, documentation, and results packaged together. Among other things, this helps to ensure that the SAS output in the document is in concordance with the code.

Literate Statistical Practice

Literate Statistical Practice (LSP, Rossini, 2001) describes an approach for creating self-documenting statistical results. It applies literate programming (Knuth, 1992) and related techniques in a natural fashion to the practice of statistics. In particular, documentation, specification, and descriptions of results are written concurrently with writing and evaluation of statistical programs. We discuss how and where LSP can be integrated into practice and illustrate this with an example derived from an actual statistical consulting project. The approach is simplified through the use of a comprehensive, open source toolset incorporating Noweb, Emacs Speaks Statistics (ESS), Sweave (Ramsey, 1994; Rossini, et al, 2002; Leisch, 2002; Ihaka and Gentlemen, 1996). We conclude with an assessment of LSP for the construction of reproducible, auditable, and comprehensible statistical analyses