Running head: FINDING STRUCTURE IN DATA 1 Draft: Finding structure in data using multivariate tree boosting. Patrick J. Miller, Gitta H. Lubke, Daniel B. McArtor, C. S. Bergeman

Source URL: arxiv.org

• Regression analysis
• Decision trees
• Statistical methods
• Econometrics
• Ensemble learning
• Nonparametric regression
• Random forest
• Decision tree learning
• Prediction
• Structural equation modeling
• Data analysis
• Decision tree

Ann Inst Stat Math:659–671 DOIs10463Optimality of pairwise blocked definitive screening designs Yaping Wang · Mingyao Ai · Kang Li

Source URL: www.ism.ac.jp

• Operations research
• Design of experiments
• Quality
• Quality control
• Statistical methods
• Mathematical optimization
• Response surface methodology
• Screening

Buy/by the Book or Bye-Bye the Game A talk for LangSec Workshop, 2016 M. Douglas McIlroy Dartmouth College

Source URL: spw16.langsec.org

• Software testing
• Software development process
• Extreme programming
• Econometrics
• Statistical methods
• Regression testing
• Regression analysis
• Unix
• Program analysis
• Computing
• Code coverage
• Analysis

Non-parametric Regression with Basis Selection from Multiple Libraries Jeffrey C. Sklar, Junqing Wu, Wendy Meiring, and Yuedong Wang ∗

Source URL: www.pstat.ucsb.edu

• Regression analysis
• Statistical methods
• Model selection
• Machine learning
• Multivariate adaptive regression splines
• Econometrics
• Stepwise regression
• Akaike information criterion
• Smoothing spline
• Bayesian information criterion

RISK EVALUATION AFTER HEART VALVE REPLACEMENT BY SAS PROC PHREG Chao L. Chen and Lynn Wang Deborah Heart and Lung Center, Browns Mills, NJSUMMARY Identification of long-term risk factors after heart valve replacem

Source URL: www.ats.ucla.edu

• Regression analysis
• Econometrics
• Statistical methods
• Statistical models
• Senescence
• Survival analysis
• Covariate
• Least squares
• Errors and residuals
• Proportional hazards model
• Propensity score matching

16 Basic Bayesian Methods Mark E. Glickman and David A. van Dyk Summary In this chapter, we introduce the basics of Bayesian data analysis. The key ingredients to a

Source URL: www.glicko.net

• Bayesian statistics
• Bayesian inference
• Prior probability
• Beta distribution
• Likelihood function
• Statistical inference
• Normal distribution
• Confidence interval
• Posterior probability
• Conjugate prior
• Marginal likelihood

Technical Note: Statistical methods for accuracy assesment of classified thematic maps D G Rossiter Department of Earth Systems Analysis

Source URL: www.css.cornell.edu

• Probability distributions
• Statistical inference
• Sampling
• Measurement
• Inter-rater reliability
• Sample size determination
• Confidence interval
• Binomial distribution
• Normal distribution
• Standard deviation
• Confusion matrix
• Statistical hypothesis testing

Decentralized Detection and Classification using Kernel Methods XuanLong Nguyen Computer Science Division University of California, Berkeley

Source URL: dept.stat.lsa.umich.edu

• Hilbert space
• Statistical classification
• Operator theory
• Positive-definite kernel
• Machine learning
• Support vector machine
• Reproducing kernel Hilbert space
• Learning
• Statistics
• Analysis
• Multiple kernel learning
• Kernel embedding of distributions

Exploring the structure of mental representations by implementing computer algorithms with people Adam N. Sanborn University of Warwick Thomas L. Griffiths

Source URL: cocosci.berkeley.edu

• Statistics
• Monte Carlo methods
• Statistical theory
• Probability
• Markov chain Monte Carlo
• Markov models
• Computational statistics
• Probability distribution
• MetropolisHastings algorithm
• Markov chain
• Normal distribution
• Hybrid Monte Carlo

3MOONS SPRING 2010 METHODOLOGY DIRECTORATE LEADING THE DEVELOPMENT OF STATISTICAL METHODS

Source URL: unstats.un.org