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School of Statistics  [21]

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Statistics is the science of learning from data. Statisticians collect, organize, analyze, interpret, and present data. We are constantly seeking better ways to do that in more and more challenging situations, using mathematics, computing, and insight. People use statistics in business, industry, medicine, government, and scientific research.

The School of Statistics at the University of Minnesota Twin Cities Campus is a leading center of statistical practice, education, and research. The School has about 19 faculty members and 60 graduate students. We offer programs leading to BA, BS, MS and PhD. degrees.

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Computing constrained Polya posterior estimates when using judgment sampling

Meeden, Glen (2013-09-25)
This is a companion to the paper "More efficient inferences using ranking information obtained from judgment sampling" by Glen Meeden and Bo Ra Lee that appeared in the Journal of Survey Statistics and Methodology in ...

Aster Models with Random Effects and Additive Genetic Variance for Fitness

Geyer, Charles J.; Shaw, Ruth G. (2013-07-10)
This technical report is a minor supplement to the paper Geyer et al. (in press) and its accompanying technical report Geyer et al. (2012). It shows how to move variance components from the canonical parameter scale to the ...

Aster Models with Random Effects via Penalized Likelihood

Geyer, Charles J.; Ridley, Caroline E.; Latta, Robert G.; Etterson, Julie R.; Shaw, Ruth G. (2012-10-09)
This technical report works out details of approximate maximum likelihood estimation for aster models with random effects. Fixed and random effects are estimated by penalized log likelihood. Variance components are estimated ...

Supplementary Material for the paper "Asymptotics for Constrained Dirichlet Distributions"

Geyer, Charles J.; Meeden, Glen (2012-06-25)
This document is supplementary material for a paper. It shows how to simulate the linear-equality-and-inequality-constrained normal distribution that is the large sample approximation to a similarly constrained Dirichlet ...

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