JMLR: Workshop and Conference Proceedings vol 40:1–22, 2015 Correlation Clustering with Noisy Partial Information Konstantin Makarychev KOMAKARY @ MICROSOFT. COM

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Points of View Syst. Biol. 58(3):346–348, 2009 c Society of Systematic Biologists Copyright
DOI:sysbio/syp040 Advance Access publication on July 17, 2009

Source URL: theoretical.univie.ac.at

• Statistics
• Covariance and correlation
• Probability theory
• Data analysis
• Correlation and dependence
• Factor analysis
• Covariance
• Partial correlation
• Modularity
• Partial least squares regression
• Morphometrics
• G factor

Supplementary Material for: Socioeconomic status predicts hemispheric specialisation of the left inferior frontal gyrus in young children Rajeev D. S. Raizada,∗1 , Todd L. Richards2 , Andrew Meltzoff1 and Patricia K. K

Source URL: www.bcs.rochester.edu

• Covariance and correlation
• Intelligence
• Psychometrics
• Independence
• Correlation and dependence
• Brodmann area 45
• G factor
• Partial correlation
• Intelligence quotient
• Functional magnetic resonance imaging
• False discovery rate
• Socioeconomic status

This article was downloaded by:[Mitteroecker, Philipp] On: 11 October 2007 Access Details: [subscription numberPublisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 107295

Source URL: theoretical.univie.ac.at

• Covariance and correlation
• Regression analysis
• Multivariate statistics
• Factor analysis
• Psychometrics
• Principal component analysis
• Covariance
• G factor
• Exploratory factor analysis
• Correlation and dependence
• Morphometrics
• Partial least squares regression

A formal theory of qualitative size and distance relations between regions Thomas Bittner1,2,3,4 and Maureen Donnelly1,3 3 1

Source URL: www.acsu.buffalo.edu

• Metric
• Metric geometry
• Topology
• Expected value
• Group theory
• Non-associative algebra
• Mathematical physics
• Partial correlation
• Mutual information

Measuring correlation risk Roza Galeeva, Jiri Hoogland, Alexander Eydeland CMG, Morgan Stanley January 11, 2007 Contents

Source URL: www.bbk.ac.uk

• Covariance and correlation
• Correlation and dependence
• Cholesky decomposition
• Multivariate normal distribution
• Covariance
• Eigenvalues and eigenvectors
• Matrix
• Bootstrapping
• Pearson product-moment correlation coefficient
• Partial correlation

Administrative Notes StatisticsLecture 7 •  Homework 1 due in recitation: Friday, Feb. 5 •  Homework 2 now posted on course website:

Source URL: www-stat.wharton.upenn.edu

• Covariance and correlation
• Statistics
• Regression analysis
• Estimation theory
• Independence
• Parametric statistics
• Correlation and dependence
• Linear regression
• Correlation does not imply causation
• Least squares
• Partial correlation
• Multiple correlation

Homework 3 solutions Joe Neeman September 22, Recall that the best linear predictor of Y given Z is and linear function of Z (say, P (Y |Z) = aZ + b) that satisfies (by the projection theorem) EP (Y |Z) = EY and

Source URL: www.stat.berkeley.edu

• Covariance and correlation
• Algebra of random variables
• Covariance
• Partial autocorrelation function

Simple connectome inference from partial correlation statistics in calcium imaging Antonio Sutera, Arnaud Joly, Vincent Fran¸cois-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst and Pierre Geurts. Goal : From time

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Homework 4 solutions Joe Neeman October 27, We began by looking at the ACF of the original data sequence (Figure 1), which seems to decay very slowly. In particular, the process is probably not an ARMA process. T

Source URL: www.stat.berkeley.edu

• Time series models
• Noise
• Time series analysis
• Covariance and correlation
• Moving-average model
• Partial autocorrelation function
• Autoregressive integrated moving average
• Akaike information criterion
• QQ plot
• BoxJenkins