EXPLORA:content interpretation of data

Most approaches to applying knowledge-based techniques for data analyses concentrate on the context-independent statistical support. EXPLORA however is developed for the subject-specific interpretation with regard to the contents of the data to be analyzed (i.e. content interpretation). Therefore its knowledge base includes also the objects and semantic relations of the real system that produces the data. In this paper we describe the functional model representing the process of content interpretation, summarize the software architecture of the system and give some examples of its applications by pilot-users in survey analysis. EXPLORA addresses applications with data produced regularly which have to be analyzed in a routine way. The system systematically searches for statistical results (facts) to detect relations which possibly could be overlooked by a human analyst. On the other hand EXPLORA will help overcome the large bulk of information which today is usually still produced when presenting the data. Therefore a second knowledge process of content interpretation consists in discovering messages about the data by condensing the facts. Approaches for inductive generalization which have been developed for machine learning are utilized to identify common values of attributes of the objects to which the facts relate. At a later stage the system searches for interesting facts by applying redundancy rules and domaindependent selection rules. EXPLORA formulates the messages in terms of the domain, groups and orders them and even provides flexible navigations in the fact spaces.     

Statistical morphology

This paper first introduces a parametric model for the generation of stationary random correlated binary sequences. The parameters of the model include the probability that a pixel is a binary one pixel and the length of the structuring element which dilates the initially spatially uncorrelated sequence. The spatial statistics of such eroded, dilated, opened and closed correlated binary sequences are derived in terms of the spatial statistics of the input binary sequence. Understanding of such one-dimensional processing is a precondition for understanding what happens in the more interesting two- dimensional case.     

A comparison of alternative rate estimators in some frequently used growth models

This paper deals with the linear, exponential and Gompertz models and compares the bias and variance of a number of estimators of the growth-rate parameters of these models. Some of these estimators have been commonly recommended in the literature and others are most frequently used in empirical practice. The present analysis points to the strengths and weaknesses of the estimators in their usage.     

ECONOMIES OF SCALE IN A MULTIPLANT TECHNOLOGY: EVIDENCE FROM THE OILPATCH

A unique micro data set detailing operating costs and technical characteristics of 133 Texas oil leases was used to estimate an econometric cost function, yielding a number of interesting findings. First, evidence of economies of scale in crude extraction implies additional gains from oil field unitization and helps explain the paradox that voluntary unitization often occurs in the later stages of a field's life. Second, marginal operating costs per well were found to be about 30 percent below average costs, explaining why many wells remain operational despite falling crude oil prices. Finally, the results confirmed a number of plausible technical relationships. For example, operating costs rise sharply with depth, explaining the existence of shallow, low-production stripper wells.     

Wage patterns: An evolutionary perspective

The existence of wage patterns is often cited as evidence that the labor market is affected by institutional forces outside the purview of economic theory. In this paper, it is argued that such patterns can be understood as the result of an information-acquiring activity of labor market participants that enhances their chance of survival. Wage comparisons are selected, sometimes mistakenly, in an effort to cope with the uncertainty of the environment. This evolutionary analysis denies a distinction between market forces and spillovers. Helpful comments on an earlier draft were received from John Pencaval, Melvin Reder, and Stanley Siebert. The usual disclaimer attaches.     

A life satisfaction measure based on judgment theory

A life satisfaction measure is developed in this paper drawn from a judgment-type theory. This measure is based on the theoretical notion of life satisfaction being a function of a comparison between perceived life accomplishments and a set of evoked standards. These standards are classified as to their derivative sources (e.g., the life accomplishments of relatives, friends, associates, past experience, self-concept of strengths and weaknesses, and average person in a similar position) and different forms (e.g., standards based on ideal, expected, deserved, minimum tolerable, and predicted outcomes). Two studies were conducted on the elderly to ascertain the internally consistent and possessing construct validity correlations through high and internally consistent and possessing construct validity correlations through high and positive correlations with the Delighted-Terrible Life Satisfaction Scale; through significant and positive correlations with cognitive age, income, employment, education, marital status, social contact, activity, religiosity, morale, television viewership, and selfrated health; and through nonsignificant correlations with chronological age, gender, and parenthood.