Relation Analysis .

• Relation Analysis

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Correlation and dependence - Further reading

1 Cohen, J., Cohen P., West, S.G., & Aiken, L.S. (2002). Applied multiple

regression/correlation analysis for the behavioral sciences (3rd ed.).

Psychology Press. ISBN 0-8058-2223-2.


Level of measurement - Debate on typology

1 This ensures that subsequent user errors cannot inadvertently perform meaningless analyses (for example correlation analysis with a variable

on a nominal level).


K-nearest neighbor algorithm - Dimension reduction

1 Feature extraction and dimension reduction can be combined in one step

using Principal Component Analysis|principal component analysis (PCA), linear discriminant analysis (LDA), or Canonical correlation|canonical correlation analysis

(CCA) techniques as a pre-processing step, followed by clustering by k-NN on Feature

(machine learning)|feature vectors in reduced-dimension space


CHARMM - CHARMM molecular dynamics program

1 More advanced features include free energy perturbation (FEP), quasi-

harmonic entropy estimation, correlation analysis and combined

quantum, and molecular mechanics (QM/MM) methods.


Time series analysis - Methods for time series analyses

1 Methods for time series analyses may be divided into two classes: frequency-domain

methods and time-domain methods. The former include frequency spectrum#Spectrum analysis|spectral analysis and recently wavelet

analysis; the latter include auto-correlation and cross-correlation analysis. In time domain correlation analyses can be made in a filter-

like manner using scaled correlation, thereby mitigating the need to operate in frequency

domain.


Time series analysis - Exploratory analysis

1 * Autocorrelation analysis to examine serial dependence


Multilinear subspace learning

1 Multilinear subspace learning#Algorithms|MSL methods are higher-order generalizations of linear subspace learning methods such as principal component analysis (PCA), linear discriminant analysis (LDA) and canonical

correlation analysis (CCA). In the literature, MSL is also referred to as tensor subspace

learning or tensor subspace analysis. Research on MSL has progressed from

heuristic exploration in 2000s (decade) to systematic investigation in 2010s.


Multilinear subspace learning - Algorithms

1 *Multilinear extension of canonical correlation

analysis|CCA



1 T.-K. Kim and R. Cipolla. [http://ieeexplore.ieee.org/xpl/article

Details.jsp?arnumber=4547427 Canonical correlation analysis of video volume tensors for action

categorization and detection], IEEE Trans. Pattern Anal. Mach. Intell., vol.

31, no. 8, pp. 1415–1428, 2009.



1 **TVP-based: Multilinear Canonical Correlation Analysis (MCCA) H. Lu,

[http://www.dsp.utoronto.ca/~haiping/Publication/MCCA_IJCAI2013.pdf Learning Canonical Correlations of Paired Tensor Sets via Tensor-to-Vector Projection], Proceedings of the 23rd International

Joint Conference on Artificial Intelligence (IJCAI 2013), Beijing, China,

August 3–9, 2013.https://store.theartofservice.com/the-relation-analysis-toolkit.html

Dimensionality reduction - Dimension reduction

1 Feature extraction and dimension reduction can be combined in one step using principal

component analysis (PCA), linear discriminant analysis (LDA), or canonical

correlation analysis (CCA) techniques as a pre-processing step followed by clustering

by K-NN on Feature (machine learning)|feature vectors in reduced-dimension

space. In machine learning this process is also called low-dimensional embedding.


Canonical correlation analysis

1 Knapp notes virtually all of the commonly encountered parametric

statistics|parametric tests of significance can be treated as special

cases of canonical-correlation analysis, which is the general

procedure for investigating the relationships between two sets of

variables


Canonical correlation analysis - Definition

1 Canonical-correlation analysis seeks vectors a and b such that the random variables a' X and b' Y

maximize the correlation \rho = \operatorname(a' X, b' Y)


Canonical correlation analysis - Derivation

1 We notice that in both cases U =V, which illustrates that the canonical-correlation analysis treats correlated and anticorrelated variables similarly.


Timing attack - Examples

1 While the number of '1' bits alone is not nearly enough information to

make finding the key trivially easy, repeated executions with the same

key and different inputs can be used to perform statistical correlation analysis of timing information to

recover the key completely, even by a passive attacker


UNISTAT

1 * Multivariate analysis: Cluster analysis, Principal components analysis, Linear discriminant analysis, canonical analysis,

Multidimensional scaling, Canonical correlation analysis


Multivariate statistics - Types of analysis

1 # Redundancy analysis (RDA) is similar to canonical correlation

analysis but allows the user to derive a specified number of synthetic

variables from one set of (independent) variables that explain

as much variance as possible in another (independent) set. It is a

multivariate analogue of Regression analysis|regression.


SigmaStat

1 The users can also conduct survival analysis, analyze rates and

proportions, perform regression and correlation analysis and calculate

power and sample size


Harold Hotelling - Statistics

1 Hotelling is known to statisticians because of Hotelling's T-squared

distribution and its use in statistical Statistical hypothesis testing|

hypothesis testing and confidence regions. He also introduced

canonical correlation analysis.


Intermarket analysis - Examples

1 This relationship decouples during times of unrest in the Middle East

and this is why it is less reliable than the relationship with energy stocks, which can be improved upon if the trades are filtered using correlation

analysis.


Quality of working life - Models and components

1 From the correlation analysis it is find that Adequacy of Resources are more correlated and Training Development

are less correlated with teaching staffs perception towards quality of worklife and in case of non teaching staffs Compensation Rewards are

more correlated and Work Environment are less correlated with

QWL.https://store.theartofservice.com/the-relation-analysis-toolkit.html

Quantitative psychological research - Examples

1 The software can then perform correlation analysis or other procedures on the data


John F. Kennedy assassination conspiracy theories - Acoustical evidence

1 Thomas, [http://www.webcitation.org/5spmKztLK Echo Correlation Analysis and the

Acoustic Evidence in the Kennedy Assassination Revisited], Science

Justice, vol


Mediation (statistics)

1 (2003) Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.)


Kernel trick

1 Algorithms capable of operating with kernels include the kernel perceptron, support vector

machines (SVM), Gaussian processes, principal components analysis (PCA), canonical correlation analysis, ridge

regression, spectral clustering, Adaptive filter|linear adaptive filters and many others. Any linear model can be turned into a non-linear model by applying the kernel trick to

the model: replacing its features (predictors) by a kernel function.


Dependency network

1 Mantegna, and Eshel Ben-Jacob (2010), Dominating clasp of the

financial sector revealed by partial correlation analysis of the stock

market, [http://dx.crossref.org/10.1371%2Fjournal.pone.0015032PLoS ONE 5(12),

e15032]Dror Y


Dependency network

1 Kenett, Matthias Raddant, Thomas Lux, and Eshel Ben-Jacob (submitted), Evolvement of

uniformity and volatility in the stressed global market, PNASEran Stark, Rotem Drori and

Moshe Abeles (2006), Partial Cross-Correlation Analysis Resolves Ambiguity in

the Encoding of Multiple Movement Features, [http://jn.physiology.org/content/95/3/1966.fu

ll.pdf J Neurophysiol 95: 1966–1975] which are becoming ever more widely used to

investigate complex systems


Discrete transform

1 In addition to frequency spectrum#Spectrum analysis|

spectral analysis of signals, discrete transforms play important role in

data compression, detection theory|signal detection, digital filtering and

correlation analysis.


Neolithic Europe - Genetic studies

1 In his 1998 study, utilising polymorphic loci from seven

hypervariable autosomal DNA loci, an autocorrelation analysis produced a clinal pattern closely matching that

in Cavalli-Sforza’s study


Lee Harvey Oswald - House Select Committee

1 Thomas, [http://www.webcitation.org/5spmKztLK Echo Correlation Analysis and the

Acoustic Evidence in the Kennedy Assassination Revisited], Science

Justice, vol


Canonical analysis - Canonical analysis

1 In this the canonical analysis differs from Harold Hotelling’s (1936) canonical variate analysis (also called the canonical correlation analysis), designed to obtain

maximum (canonical) correlations between the predictor and criterion

canonical variates


Dictabelt evidence relating to the assassination of John F. Kennedy - Further reading

1 *Thomas, Donald B. (14 June 2000). [http://web.archive.org/web/2008100

1192848/http://www.forensic-science-society.org.uk/Thomas.pdf Echo correlation analysis and the acoustic evidence in the Kennedy assassination revisited.] Science

Justice 2001 '41', 21-32.


Aquaculture of salmon - Impact on wild salmonids

1 However, these studies are all correlation analysis and correlation doesn't equal causation, especially when similar salmon declines were occurring in Oregon and California,

which have no salmon aquaculture or marine net pens


Particle image velocimetry - Camera

1 This has allowed each exposure to be isolated on its own frame for more

accurate cross-correlation analysis


Sound localization

1 The sound localization mechanisms of the mammalian auditory system have been extensively studied. The auditory system uses several cues

for sound source localization, including time- and level-differences

between both ears, spectral information, timing analysis,

correlation analysis, and pattern matching.


Hennen's American Public Library Ratings - United States

1 The four statistics, library visits, circulation, program attendance, and public internet computer uses, were chosen based on correlation analysis


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