Statistical analysis of DNA mixtures is known to pose computational challenges due to the enormous state space of possible DNA profiles. We propose a Bayesian network representation for genotypes, allowing computations to be performed locally involving only a few alleles at each step. In addition, we describe a general method for computing the expectation of a product of discrete random variabl...

ggmcmc is an R package for analyzing Markov chain Monte Carlo simulations from Bayesian inference. By using a well known example of hierarchical/multilevel modeling, the article reviews the potential uses and options of the package, ranging from classical convergence tests to caterpillar plots or posterior predictive checks. This R vignette is based on the article published at the Journal of St...

We propose a Bayesian approach for assessing the reliability of multicomponent systems. Our models allow us to evaluate system, subsystem, and component reliability using the available multilevel information. Data are collected over time, and include pass/fail, lifetime, censored, and degradation data. We illustrate the methodology through an example and discuss how to extend the approach to mo...

Research in marketing, and business in general, involves understanding when effect-sizes are expected to be large and when they are expected to be small. An example is the level-effect in marketing, where the effect of product attributes on utility is positively related to the number of levels present among choice alternatives. Knowing when consumers are sensitive to the levels of attributes is...

Correlated data are fairly common in health and social sciences. For example, clustered data arise when subjects are nested in clusters such as classrooms, hospitals, and neighborhoods; while longitudinal data result from multiple measures for the same subject over long period of time; whereas repeated measures data are involved in multiple measurements for the same subject over time or other d...

We employed a multilevel hierarchical Bayesian model in the task of exploiting relevant interactions among high cardinality attributes in a classification problem without overfitting. With this model, we calculate posterior class probabilities for a pattern W combining the observations of W in the training set with prior class probabilities that are obtained recursively from the observations of...

Building intelligent environment is one of crucial challenges for ubiquitous computing developers. To make the environment adapt rationally according to the desire of users, the system should be able to guess users’ interest, by learning users’ behavior, habit or preference. While learning the user preference, dealing with uncertainty and conflict resolution is of the utmost importance. When ma...

This paper proposes a hybrid carrier based space vector modulation suitable for multiphase multilevel inverters. Multiphase multilevel inverters are controlled by this hybrid modulation to provide multiphase variable voltage and variable frequency supply. The proposed modulation inherits the features of fundamental frequency modulation and carrier based space vector modulation strategies. The m...