The generalized Dirichlet distribution has been shown to be a more appropriate prior for naı̈ve Bayesian classifiers, because it can release both the negative-correlation and the equal-confidence requirements of the Dirichlet distribution. The previous research did not take the impact of individual attributes on classification accuracy into account, and therefore assumed that all attributes foll...

Introduction ...................................................................................................................................................1 Experimental Design: Sampling Number and Frequency.............................................................................2 Sampling Plans ..............................................................................................

Recently we have witnessed a welcomed increase in the amount of empirical evaluation of Software Engineering methods and concepts. It is hoped that this increase will lead to establishing Software Engineering as a well-deened subject with a sound scientiically proven underpinning rather than a topic based upon unsubstantiated theories and personal belief. For this to happen the empirical work m...

A fundamental question within the field of program evaluation is “Do social programs work?” Although experiments allow us to answer this question with certainty, they have some limitations. Experiments generate mean program impacts and even mean impacts by subgroup, but they often leave unexplored the impacts on subgroups determined by treatment use. This work proposes a methodology for analyzi...

This vignette is intended to give a rapid introduction to the commands used in implementing two methods of evaluating differential expression in Solexa-type, or count data by means of the baySeq R package. For fuller details on the methods being used, consult Hardcastle & Kelly [1]. The major improvement made in this release is the option to include region length in evaluating differential expr...

Screening experiments are addressed to the identiication of the relevant variables within some process or experimental outcome potentially depending on a large number of variables. In this paper we introduce a new class of experimental designs called edge designs. These designs are very useful for screening experiments since they allow a model-independent estimate of the set of relevant variabl...

ingle-case research designs are a diverse and powerful set of procedures useful for demonstrating causal relations among clinical phenomena. Although such designs are flexible, efficient, and have been used to make key advances since the earliest days of psychological science, they are currently extremely underused by psychological scientists and clinicians. We review the historical and theoret...