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Title: EMG Pattern Analysis Using Principal Component Analysis Author: Bill Rose Created Date: 10/20/2006 5:08:07 PM Document presentation format

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PCA looks for a transformation of the xi into p new variables yi that are ... We use the kurtosis of the variables to approximate the distribution function ...

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Data set 2, Std. deviation = 1.58. Measure of the spread of data in a data set. Example: ... Result: value is not as important as its sign ...

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PCA results. In this simple example, the EOFs may be interpreted as ... Example: national lottery results. Are there patterns in lottery results? ...

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Principal components is about explaining the variance-covariance ... Recommend Keep defaults but also check 'Scree plot'. Example of Factor Analysis: Rotation ...

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A typical use of factor analysis is in survey research, where a ... Recommend Keep defaults but also check 'Scree plot'. Example of Factor Analysis: Rotation ...

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Scree plot is the plot of the eigenvalues against their indices. For example plot given by R. ... screeplot(pc1) - gives scree plot. biplot(pc1) gives biplot. or ...

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so that it has maximum possible variance. ... It is the projection of observation vectors and variables to k p dimensional space. ...

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to request the unrotated factor solution and a scree plot of the eigenvalues. ... Plot of total variance - Scree plot. Gradual trailing off of variance ...

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Each fMRI study contains a huge number of voxel time series (70 000 100 000 or ... Two data sets were created: one set where the response in area 2 was independent ...

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Factor Analysis An Alternative technique for studying correlation and covariance structure Extracting the Factors Several Methods we consider two Principal ...

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Clustering Algorithms. Principal Components Analysis. Outline ... It is a very interactive algorithm allows users to dynamically change ...

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Pathway Analysis Goals Characterize biological meaning of joint changes in gene expression Organize expression (or other) changes into meaningful chunks (themes ...

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