Current Search:  Uncertainty Information theory (x)

View All Items

  • CSV Spreadsheet
(1 - 2 of 2)
USE OF CERTAINTY EQUIVALENCE FOR LOCATION AND ECONOMIC GROWTH DECISIONS
Title
THE USE OF CERTAINTY EQUIVALENCE FOR LOCATION AND ECONOMIC GROWTH DECISIONS.
Creator
WONSETLER, ELIZABETH ANN., Florida Atlantic University, Scheidell, John M., College of Business, Department of Economics
Abstract/Description
This study was prepared to analyze the use of the first-period certainty equivalence procedure in location decisions. Certainty equivalence is a mathematical technique which explicitly incorporates probablistic uncertainty in the decision making process. The feasible location of an international jetport which would service the South Florida region is used to illustrate this decision making technique.
Date Issued
1972
PURL
http://purl.flvc.org/fcla/dt/13473
Subject Headings
Decision-making--Mathematical models, Uncertainty (Information theory)
Format
Document (PDF)
min/max algorithm for cubic splines over k-partitions
Title
A min/max algorithm for cubic splines over k-partitions.
Creator
Golinko, Eric David, Charles E. Schmidt College of Science, Department of Mathematical Sciences
Abstract/Description
The focus of this thesis is to statistically model violent crime rates against population over the years 1960-2009 for the United States. We approach this question as to be of interest since the trend of population for individual states follows different patterns. We propose here a method which employs cubic spline regression modeling. First we introduce a minimum/maximum algorithm that will identify potential knots. Then we employ least squares estimation to find potential regression...
Show moreThe focus of this thesis is to statistically model violent crime rates against population over the years 1960-2009 for the United States. We approach this question as to be of interest since the trend of population for individual states follows different patterns. We propose here a method which employs cubic spline regression modeling. First we introduce a minimum/maximum algorithm that will identify potential knots. Then we employ least squares estimation to find potential regression coefficients based upon the cubic spline model and the knots chosen by the minimum/maximum algorithm. We then utilize the best subsets regression method to aid in model selection in which we find the minimum value of the Bayesian Information Criteria. Finally, we preent the R2adj as a measure of overall goodness of fit of our selected model. We have found among the fifty states and Washington D.C., 42 out of 51 showed an R2adj value that was greater than 90%. We also present an overall model of the United States. Also, we show additional applications our algorithm for data which show a non linear association. It is hoped that our method can serve as a unified model for violent crime rate over future years.
Show less
Date Issued
2012
PURL
http://purl.flvc.org/FAU/3342107
Subject Headings
Spline theory, Data processing, Bayesian statistical decision theory, Data processing, Neural networks (Computer science), Mathematical statistics, Uncertainty (Information theory), Probabilities, Regression analysis
Format
Document (PDF)