Bayesian inference for fault based software reliability models given software metrics data

We wish to predict the number of faults N and the time to next failure of a piece of software. Software metrics data are used to estimate the prior mean of N via a Poisson regression model. Given failure time data and a some well known fault based models for interfailure times, we show how to sample the relevant posterior distributions via Gibbs sampling using the package Winbugs. Our approach is illustrated with an example

Bayesian inference for a software reliability model using metrics information.

In this paper, we are concerned with predicting the number of faults N and the time to next failure of a piece of software. Information in the form of software metrics data is used to estimate the prior distribution of N via a Poisson regression model. Given failure time data, and a well known model for software failures, we show how to sample the posterior distribution using Gibbs sampling, as implemented in the package "WinBugs". The approach is illustrated with a practical example

BAYESIAN INFERENCE FOR A SOFTWARE RELIABILITY MODEL USING METRICS INFORMATION.

In this paper, we are concerned with predicting the number of faults N and the time to next failure of a piece of software. Information in the form of software metrics data is used to estimate the prior distribution of N via a Poisson regression model. Given failure time data, and a well known model for software failures, we show how to sample the posterior distribution using Gibbs sampling, as implemented in the package "WinBugs". The approach is illustrated with a practical example.

Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis

Multiple testing analysis, based on clustering methodologies, is usually applied in Microarray Data Analysis for comparisons between pair of groups. In this paper, we generalize this methodology to deal with multiple comparisons among more than two groups obtained from microarray expressions of genes. Assuming normal data, we define a statistic which depends on sample means and sample variances, distributed as a non-central t-distribution. As we consider multiple comparisons among groups, a mixture of non-central t-distributions is derived. The estimation of the components of mixtures is obtained via a Bayesian approach, and the model is applied in a multiple comparison problem from a microarray experiment obtained from gorilla, bonobo and human cultured fibroblasts.Clustering, MCMC computation, Microarray analysis, Mixture distributions, Multiple hypothesis testing, Non-central t-distribution

Noblessa i poder al monestir de Santa Maria del Pedregal a l'edat mitjana

Durant l'edat mitjana, la noblesa ocupa un rol fonamental en l'organització i el control de la societa

Sánchez Mejías, cronista taurino

Ignacio Sánchez Mejías. Periodista y dramaturgo. Seminari

Folc II, vescomte de Cardona, bisbe electe d'Urgell i bisbe de Barcelona (c.1040-1099)

Aquest treball ressegueix la biografia de Folc II, vescomte de Cardona, bisbe eslecte d'Urgell i bisbe de Barcelona. Folc era fill del vescomte Folc I de Cardona i de Guisla, procedent de la família vescomtal de Barcelona, Tot partint d'una important recopilació documental (més de 70 documents) i d'altres fonts de diferent natura (iconogràfiqes, numismàtiques...) és possible arribar a una acurada contextualització del personatge, que ens permet de comprendre millor els primers passos de la Reforma Gregoriana i els conflictes nobiliaris de la segona meitat del segle XI a Cataluny