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In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space. The procedure thus appears to be the counterpart of principal component analysis for ...
It approximates the value of a function at an intermediate point (,,) within the local axial rectangular prism linearly, using function data on the lattice points. Trilinear interpolation is frequently used in numerical analysis, data analysis, and computer graphics.
If we use the matrix notation for the common case =, we can express the equation in a more friendly manner: = [] [] [] for between 0 and 1 for one dimension. Note that for 1-dimensional cubic convolution interpolation 4 sample points are required.
For data requests that fall between the table's samples, an interpolation algorithm can generate reasonable approximations by averaging nearby samples." [8] In data analysis applications, such as image processing, a lookup table (LUT) can be used to transform the input data into a more desirable output format. For example, a grayscale picture ...
Commutation matrix: The matrix of the linear map that maps a matrix to its transpose: See Vectorization: Duplication matrix: The matrix of the linear map mapping the vector of the distinct entries of a symmetric matrix to the vector of all entries of the matrix: See Vectorization: Elimination matrix
For a symmetric matrix A, the vector vec(A) contains more information than is strictly necessary, since the matrix is completely determined by the symmetry together with the lower triangular portion, that is, the n(n + 1)/2 entries on and below the main diagonal.
A matrix with the same number of rows and columns is called a square matrix. [5] A matrix with an infinite number of rows or columns (or both) is called an infinite matrix. In some contexts, such as computer algebra programs, it is useful to consider a matrix with no rows or no columns, called an empty matrix.
A bilinear map is a function: such that for all , the map (,) is a linear map from to , and for all , the map (,) is a linear map from to . In other words, when we hold the first entry of the bilinear map fixed while letting the second entry vary, the result is a linear operator, and similarly for when we hold the second entry fixed.