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In mathematics, a block matrix or a partitioned matrix is a matrix that is interpreted as having been broken into sections called blocks or submatrices. [1] [2]Intuitively, a matrix interpreted as a block matrix can be visualized as the original matrix with a collection of horizontal and vertical lines, which break it up, or partition it, into a collection of smaller matrices.
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The block bootstrap is used when the data, or the errors in a model, are correlated. In this case, a simple case or residual resampling will fail, as it is not able to replicate the correlation in the data. The block bootstrap tries to replicate the correlation by resampling inside blocks of data (see Blocking (statistics)). The block bootstrap ...
In mathematics, a coefficient is a multiplicative factor in some term of a polynomial, a series, or any expression. For example, in the polynomial 7 x 2 − 3 x y + 1.5 + y , {\displaystyle 7x^{2}-3xy+1.5+y,} with variables x {\displaystyle x} and y {\displaystyle y} , the first two terms have the coefficients 7 and −3.
In mathematics, the determinant is a scalar-valued function of the entries of a square matrix.The determinant of a matrix A is commonly denoted det(A), det A, or | A |.Its value characterizes some properties of the matrix and the linear map represented, on a given basis, by the matrix.
In mathematics, a combination is a selection of items from a set that has distinct members, such that the order of selection does not matter (unlike permutations).For example, given three fruits, say an apple, an orange and a pear, there are three combinations of two that can be drawn from this set: an apple and a pear; an apple and an orange; or a pear and an orange.
The volume of a ship's hull below the waterline (solid), divided by the volume of a rectangular solid (lines) of the same length, height and width, determine a ship's block coefficient. Coefficients [5] help compare hull forms as well: Block coefficient (C b) is the volume (V) divided by the L WL × B WL × T WL. If you draw a box around the ...
The model for a randomized block design with one nuisance variable is = + + + where Y ij is any observation for which X 1 = i and X 2 = j X 1 is the primary factor X 2 is the blocking factor μ is the general location parameter (i.e., the mean)