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Parallel analysis, also known as Horn's parallel analysis, is a statistical method used to determine the number of components to keep in a principal component analysis or factors to keep in an exploratory factor analysis. It is named after psychologist John L. Horn, who created the method, publishing it in the journal Psychometrika in 1965. [1]
Analysis of parallel algorithms is usually carried out under the assumption that an unbounded number of processors is available. This is unrealistic, but not a problem, since any computation that can run in parallel on N processors can be executed on p < N processors by letting each processor execute multiple units of work.
emmtrix Parallel Studio is a source-to-source parallelization tool combined with an interactive GUI developed by emmtrix Technologies GmbH. It takes C, MATLAB, Simulink, Scilab or Xcos source code as input and generates parallel C code as output. It relies on static schedule and a message passing API for the parallel program.
Loop-level parallelism is a form of parallelism in software programming that is concerned with extracting parallel tasks from loops.The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures.
In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables. [ 1 ]
Based on the research and work on parallel tree contraction, various algorithms have been proposed targeting to improve the efficiency or simplicity of this topic. This article hereby focuses on a particular solution, which is a variant of the algorithm by Miller and Reif, and its application.
Pages in category "Analysis of parallel algorithms" The following 13 pages are in this category, out of 13 total. This list may not reflect recent changes. ...
In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. [1] The scree plot is used to determine the number of factors to retain in an exploratory factor analysis (FA) or principal components to keep in a principal component analysis (PCA).