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Associate Professor Paul Velleman,Department of Statistical Science at Cornell University（图）
Department of Statistical Science at Cornell University Associate Professor Social Statistics
2015/8/14
Paul Velleman is an Associate Professor of Social Statistics in the Industrial and Labor Relations School. His research is focused on Distance and Online Learning, Healthcare, abd Statistical Theory, ...
Professor Martin Wells,Department of Statistical Science at Cornell University（图）
Department of Statistical Science at Cornell University Professor Social Statistics
2015/8/14
Martin T. Wells, Ph.D., joined the Cornell faculty in 1987 and is the Charles A. Alexander Professor of Statistical Sciences. He is also a Professor of Social Statistics, Professor of Clinical Epidemi...
Statistical Model Building, Machine Learning, and the Ah-Ha Moment
Statistical Model Building Machine Learning the Ah-Ha Moment
2013/4/28
The Committee of Presidents of Statistical Societies (COPSS) will celebrate its 50th Anniversary in 2013. As part of its celebration, COPSS intends to publish a book with contributions from the past r...
Statistical Inference For Persistent Homology
persistent homology topology density estimation
2013/4/28
Persistent homology is a method for probing topological properties of point clouds and functions. The method involves tracking the birth and death of topological features as one varies a tuning parame...
From GWAS to transcriptomics in prospective cancer design - new statistical challenges
Post -GWAS Transcriptomics Nested case -control Functional changes Biomarkers
2013/4/27
Background. With the increasing interest in post-GWAS research which represents a transition from genome-wide association discovery to analysis of functional mechanisms, attention has been lately focu...
Statistical Topic Models for Multi-Label Document Classification
Topic Models LDA Multi-Label Classification Document Modeling
2011/7/19
Machine learning approaches to multi-label document classification have (to date) largely relied on discriminative modeling techniques such as support vector machines. A drawback of these approaches i...
Statistical Distribution of Crystallographic Groups for Inorganic Crystal Structure Database
Statistical Distribution Crystallographic Groups Inorganic Crystal Structure Database
2011/7/6
We introduce a method that defines the species (representatives) of inorganic compounds, and studied the statistical distribution of the defined species among space groups (distribution of space group...
Statistical Inference: The Big Picture
Bayesian confidence frequentist statistical education
2011/7/5
Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results?
Rejoinder: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
Quantifying Genetic Studies Missing Information Hypothesis Testing
2011/3/21
Rejoinder to "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
Statistical Methods for Analyzing Tissue Microarray Images - Algorithmic Scoring and Co-training
Statistical Methods Analyzing Tissue Microarray Images Algorithmic Scoring Co-training
2011/3/18
Recent advances in tissue microarray technology have allowed immuno-histochemistry to become a powerful medium-to-high throughput analysis tool, particularly for the validation of diagnostic and progn...
Comment: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
Quantifying Statistical Genetic Studies
2011/3/21
Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
Comment: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
Quantifying Statistical Genetic Studies
2011/3/21
Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
On statistical uncertainty in nested sampling
uncertainty Nested sampling Bayesian analysis
2011/3/25
Nested sampling has emerged as a valuable tool for Bayesian analysis, in particular for determining the Bayesian evidence. The method is based on a specific type of random sampling of the likelihood f...