Chapter 4: Methods Any empirical or statistical approach to groundwater vulnerability analysis proceeds from the assumption that high concentrations of contaminants are found more often where vulnerability is high than w

Source URL: www.ce.utexas.edu

• Water
• Optical materials
• Natural resources
• Geotechnical engineering
• Hydraulic engineering
• Hydrology
• Liquid water
• Groundwater pollution
• Water quality
• Contamination
• Groundwater
• Social vulnerability

AWARDS & ANNOUNCEMENTS Dr. Lee Dicker Dense and Sparse Methods in High-Dimensional Data Analysis Many statistical methods for high-dimensional data analysis begin with the assumption that the parameter of interest is, i

Source URL: statistics.rutgers.edu

Published as "A Test of the Normality Assumption in the Ordered Probit Model," 1996, METRON, LIV:A Test of the Normality Assumption in the Ordered Probit Model‡ Paul A. Johnson

Source URL: irving.vassar.edu

• Latin script
• Probit
• Normal distribution
• Ñ
• Œ
• Anglo-Saxon runes
• N
• Statistical hypothesis testing
• Statistics
• Econometrics
• ISO 15924

CHANCE: ?JEW D I R E C T I O N S F O R S T A T I S T I C S AND C014PUTING 3 ( 3 ) : , A genetic pattern matching technique is being used to iden ti* individuals. An assumption o f statistical independe

Source URL: lab.rockefeller.edu

2010 International Conference on Pattern Recognition The binormal assumption on precision-recall curves Kay H. Brodersen∗† , Cheng Soon Ong∗ , Klaas E. Stephan† and Joachim M. Buhmann∗ ∗ Department † Insti

Source URL: people.inf.ethz.ch

• Differential geometry
• Curves
• Machine learning
• Receiver operating characteristic
• Differential geometry of curves
• Frenet–Serret formulas
• Normal distribution
• Sensitivity and specificity
• Binary classification
• Statistics
• Biostatistics
• Statistical classification

Robustness of population size estimates against violation of the independence assumption Susanna C. Gerritse University Utrecht Peter G. M. van der Heijden

Source URL: www.statistics.gov.hk

• Statistical theory
• Statistical inference
• Maximum likelihood
• Estimator
• Entailment
• Estimation theory
• Logic
• Statistics

Local independence Jeroen K. Vermunt & Jay Magidson Local independence is the basic assumption underlying latent variable models, such as factor analysis, latent trait analysis, latent class analysis, and latent profile

Source URL: statisticalinnovations.com

• Statistical dependence
• Categorical data
• Econometrics
• Local independence
• Latent class model
• Latent variable model
• Item response theory
• Factor analysis
• Latent variable
• Statistics
• Statistical models
• Psychometrics

6.867 Machine learning, lecture 3 (Jaakkola) 1 The Support Vector Machine So far we have used a reference assumption that there exists a linear classifier that has

Source URL: ocw.mit.edu

• Mathematical optimization
• Statistical classification
• Operations research
• Support vector machine
• Vector space
• Perceptron
• Quadratic programming
• Algebra
• Mathematics
• Statistics

Collaborative Filtering and the Missing at Random Assumption Benjamin M. Marlin Richard S. Zemel Yahoo! Research and Department of

Source URL: www.cs.toronto.edu

• Cluster analysis
• Collaborative filtering
• Social information processing
• Mixture model
• Expectation–maximization algorithm
• Recommender system
• Conjugate prior
• Statistical model
• Maximum likelihood
• Statistics
• Estimation theory
• Statistical theory

2010 International Conference on Pattern Recognition The binormal assumption on precision-recall curves Kay H. Brodersen∗† , Cheng Soon Ong∗ , Klaas E. Stephan† and Joachim M. Buhmann∗ ∗ Department † Insti

Source URL: www.ong-home.my

• Differential geometry
• Curves
• Machine learning
• Receiver operating characteristic
• Differential geometry of curves
• Frenet–Serret formulas
• Normal distribution
• Sensitivity and specificity
• Binary classification
• Statistics
• Biostatistics
• Statistical classification