Agricultural Land Use Planning and Groundwater Quality

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75123/1/j.1468-2257.1983.tb00394.x.pd

Fitting Second-Order Finite Mixture Models to Data with Many Censored Values Using Maximum Likelihood Estimation

Abstract Finite mixture models, i.e., weighted averages of parametric distributions, provide a powerful way to extend parametric families of distributions to fit data sets not adequately fit by a single parametric distribution. First-order finite mixture models have been widely used in the physical, chemical, biological, and social sciences for over 100 years. Using maximum likelihood estimation, we demonstrate how a first-order finite mixture model can represent the large variability in data collected by the US Environmental Protection Agency for the concentration of Radon 222 in drinking water supplied from ground water, even when 28 percent of the data fall at or below the Minimum Reporting Level. Extending the use of maximum likelihood, we also illustrate how a second-order finite mixture model can separate and represent both the variability and the uncertainty in the data set

Boston Community Information System - 1986 Experimental Test Results

This report describes the first year of an experimental test of the Boston Community Information System (Boston CommInS). The experiment implements new ideas of data communication and database design in the transmission and reception of data. The system offers the Associated Press and New York Times to participants and is provided in exchange for their monthly feedback

Boston Community Information System User's Manual

The Boston Community Information System turns your computer into a personal information assistant that monitors the news as it happens. This experiment, CommInS, tests a new way of distributing world news as it happens and features from the New York Times and the Associate Press wire service directly to personal computers via radio waves