Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Asymptotic Confidence Interval (1)
- Baseball (1)
- Bootstrap Confidence Interval (1)
- Citation Network (1)
- Conditional Random Fields (1)
-
- Dominance Analysis (1)
- Generalizability Theory (1)
- Graph Analysis (1)
- Machine Learning (1)
- Markov (1)
- Non-Normal Distribution (1)
- Pareto Distribution (1)
- Peer Assessment (1)
- Positive Dependent Risks (1)
- Protein-protein Interaction (1)
- Rater Reliability (1)
- Reinsurance (1)
- Self Assessment (1)
- Social Network (1)
- Urban (1)
- Validity (1)
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
A Markov Model For Baseball With Applications, Daniel Joseph Ursin
A Markov Model For Baseball With Applications, Daniel Joseph Ursin
Theses and Dissertations
In this work we confirm a Markov chain model of baseball for 2013 Major League Baseball batting data. We describe the transition matrices for individual player data and their use in generating single and nine-inning run distributions for a given lineup. The run distribution is used to calculate the expected number of runs produced by a lineup over nine innings. We discuss batting order optimization heuristics to avoid computation of distributions for the 9! = 362, 880 distinct lineups for 9 players. Finally, we describe an implementation of the algorithms and review their performance against actual game data.
Inferential Procedures For Dominance Analysis Measures In Multiple Regression, Shuwen Tang
Inferential Procedures For Dominance Analysis Measures In Multiple Regression, Shuwen Tang
Theses and Dissertations
In order to better interpret a selected multiple regression model, researchers are often interested in whether a predictor is significantly more important than another or not. This study investigates the performance of the Normal-Theory based (asymptotic) confidence interval and bootstrap confidence intervals for predictors' dominance relationships using both normal and non-normal data. The results show that asymptotic confidence interval method is adequate to make inferences for comparing two general dominance measures when the distribution is multivariate normal or slightly non-normal and when the effect size is no less than 0.15 and the sample size is at least 100. However, the …
Complex Network Analysis For Scientific Collaboration Prediction And Biological Hypothesis Generation, Qing Zhang
Complex Network Analysis For Scientific Collaboration Prediction And Biological Hypothesis Generation, Qing Zhang
Theses and Dissertations
With the rapid development of digitalized literature, more and more knowledge has been discovered by computational approaches. This thesis addresses the problem of link prediction in co-authorship networks and protein--protein interaction networks derived from the literature. These networks (and most other types of networks) are growing over time and we assume that a machine can learn from past link creations by examining the network status at the time of their creation. Our goal is to create a computationally efficient approach to recommend new links for a node in a network (e.g., new collaborations in co-authorship networks and new interactions in …
Validity And Rater Reliability Of Peer And Self Assessments For Urban Middle School Students, Lucas Jackson
Validity And Rater Reliability Of Peer And Self Assessments For Urban Middle School Students, Lucas Jackson
Theses and Dissertations
This project studied the validity and reliability of self and peer assessments used for group work. The targeted population is middle school students in urban schools. The sample includes 45 sixth graders selected from a public middle school in a large Midwestern metropolitan area. The students worked in groups to complete a classroom project. Self and peer assessment forms were used to rate each member's contribution to the group work. A Generalizability Theory design was used to evaluate the reliability of self and peer assessments. The validity of student ratings was assessed by comparing them to those assigned by the …
Optimal Reinsurance Strategy With Bivariate Pareto Risks, Evelyn Susanne Gaus
Optimal Reinsurance Strategy With Bivariate Pareto Risks, Evelyn Susanne Gaus
Theses and Dissertations
In an insurance, one is often concerned with risks and extreme events which can cause large losses. The Pareto distribution is often used in actuarial sciences for modeling large losses. This thesis extends the study of Cai and Wei (2011) by considering a two-line business model with positive dependence through stochastic ordering (PDS) risks, where the risks are bivariate Pareto distributed. Cai and Wei (2011) showed that in individual reinsurance treaties the excess-of-loss treaty is the optimal reinsurance form for an insurer with PDS risks. We derive explicit expressions for the optimal retention levels in the excess-of-loss treaty by considering …