This article describes and demonstrates the BayesSDT MATLAB-based software package for performing Bayesian analysis with equal-variance Gaussian signal detection theory (SDT). The software uses WinBUGS to draw samples from the posterior distribution of six SDT parameters: discriminability, hit rate, false alarm rate, criterion, and two alternative measures of bias. The software either provides ...

BUGS is a software project that began in Cambridge, England, and has been actively ongoing for more than twenty years. Its core purpose is to provide a computational companion to Bayesian statistical analyses, and the software makes extensive use of Markov chain Monte Carlo and similar simulation methods. At present the software exists in a number of versions, such as WinBUGS, OpenBUGS, and JAG...

Graphical models have been widely used to describe complex statistical models and to communicate these models to people who do not have a statistical background. In this paper we discus the WinBUGS software package which is based on these two ideas. A declarative language, the BUGS language, has been developed to describe complex statistical models. This language is processed by a compiler to p...

Based on former work on automatic transcription of musical time series into sheet music (Ligges et al. (2002), Weihs and Ligges (2003, 2005)) in this paper parameters of the transcription algorithm are optimized for various real singers. Moreover, the parameters of various artificial singer models derived from the models of Rossignol et al. (1999) and Davy and Godsill (2002) are estimated. In b...

Bayesian data analysis includes but is not limited to Bayesian inference (Gelman et al., 2003; Kerman, 2006a). Here, we take Bayesian inference to refer to posterior inference (typically, the simulation of random draws from the posterior distribution) given a fixed model and data. Bayesian data analysis takes Bayesian inference as a starting point but also includes fitting a model to different ...

If, in the mid 1980’s, one had asked the average statistician about the difficulties of using Bayesian Statistics, his/her most likely answer would have been “Well, there is this problem of selecting a prior distribution and then, even if one agrees on the prior, the whole Bayesian inference is simply impossible to implement in practice!” The same question asked in the 21th Century does not pro...

Elicitator : an expert elicitation tool for regression in ecology. Abstract. Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a fo...

Abstract The study of system safety and reliability has always been vital for the quality manufacturing engineers varying fields which generally continuous probability distributions are proposed. Bivariate multivariate candidates while studying more than one characteristic system. In this article, an attempt is made to address issue when systems generate bivariate correlated count datasets. gen...