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A biplot is constructed by using the singular value decomposition (SVD) to obtain a low-rank approximation to a transformed version of the data matrix X, whose n rows are the samples (also called the cases, or objects), and whose p columns are the variables.
A biplot is in fact a low dimensional mapping of a part of the information contained in the original table. As a rule of thumb that set (rows or columns) which should be analysed with respect to its composition as measured by the other set is displayed in principal coordinates while the other set is displayed in standard coordinates.
A generalised biplot displays information on both continuous and categorical variables. Bland–Altman plot : In analytical chemistry and biostatistics this plot is a method of data plotting used in analysing the agreement between two different assays .
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
A sample scree plot produced in R.The Kaiser criterion is shown in red.. In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. [1]
The beta negative binomial distribution; The Boltzmann distribution, a discrete distribution important in statistical physics which describes the probabilities of the various discrete energy levels of a system in thermal equilibrium.
A plot showing 100 random numbers with a "hidden" sine function, and an autocorrelation (correlogram) of the series on the bottom. In the analysis of data, a correlogram is a chart of correlation statistics.
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