Overview: Categorical Data and Graphics Methods for discrete distributions – testing goodness of fit Hanging rootograms Robust distribution plots Methods for two-way frequency tables – understanding association Fourfold displays Sieve diagrams Mosaic displays and loglinear models for n-way tables Mosaic displays Mosaic matrices Correspondence analysis and MCA Logistic and logit regression Logit...

There is a growing interest in languages that combine probabilistic models with logic to represent complex domains involving uncertainty. Causal probabilistic logic (CP-logic), which has been designed to model causal processes, is such a probabilistic logic language. This paper investigates inference algorithms for CP-logic; these are crucial for developing learning algorithms. It proposes a ne...

Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials can be used to approximate utility functions. This paper introduces MTE influence diagrams, which can represent decision problems without restrictions on the relationships between continuous and discrete chance variable...

Refinement is fundamental to software development. An earlier work proposed a refinement relation between sequence diagrams based on their required behaviors. In this paper, we first generalize the refinement relation by taking into account system variable assignment and event hiding, renaming and substitution. We then give an algorithm as a system of inference rules that does not just verify r...

We present the results of a morphological study performed to a sample of Ultracompact (UC) H II regions with Extended Emission (EE) using Spitzer–IRAC imagery and 3.6 cm VLA conf. D radio-continuum (RC) maps. Some examples of the comparison between maps and images are presented. Usually there is an IR point source counterpart to the peak(s) of RC emission, at the position of the UC H II source....

Decision-making under dynamic environments is an important problem frequently encountered in the practice. In this paper, we reveal some properties of value of information in dynamic environment, and compare the results with that in different representations by other researchers. We study the time invariant features in dynamic influence diagrams (DID) to enhance the value of information calcula...

There exist several architectures to solve influence diagrams using local computations, such as the Shenoy-Shafer, the HUGIN, or the Lazy Propagation architectures. They all extend usual variable elimination algorithms thanks to the use of so-called “potentials”. In this paper, we introduce a new architecture, called the Multi-operator Cluster DAG architecture, which can produce decompositions ...

Three experiments examined the role of step-by-step and final-state diagrams in supporting object assembly. A total of 180 college students made origami objects from instructions consisting of text only, text plus a final-state (completed-object) diagram, or text plus step-by-step and final-state diagrams. In Experiments 1 and 2, construction accuracy in the final-diagram condition was comparab...

Influence diagrams and decision trees represent the two most common frameworks for specifying and solving decision problems. As modeling languages, both of these frameworks require that the decision analyst specifies all possible sequences of observations and decisions (in influence diagrams, this requirement corresponds to the constraint that the decisions should be temporarily linearly ordere...