mathematics, particularly matrix theory, the n×n Lehmer matrix (named after Derrick Henry Lehmer) is the constant symmetric matrix defined by A i j = { i...

Derrick Henry "Dick" Lehmer (February 23, 1905 – May 22, 1991), almost always cited as D.H. Lehmer, was an American mathematician significant to the development...

matrices used in mathematics, science and engineering. A matrix (plural matrices, or less commonly matrixes) is a rectangular array of numbers called entries...

covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the...

Jordan normal form A skyline matrix, also called "variable band matrix" – a generalization of band matrix The inverses of Lehmer matrices are constant tridiagonal...

Henry Lehmer, a rather fast GCD algorithm Lehmer matrix, in mathematics, named after Derrick Henry Lehmer Lehmer mean, named after Derrick Henry Lehmer Lehmer...

engine Lucas–Lehmer primality test for Mersenne numbers Cholesky decomposition, an algorithm to decompose matrix A into a lower Matrix L : A = LLT. Linus...

In mathematics and in particular in combinatorics, the Lehmer code is a particular way to encode each possible permutation of a sequence of n numbers....

Lehmer's GCD algorithm, named after Derrick Henry Lehmer, is a fast GCD algorithm, an improvement on the simpler but slower Euclidean algorithm. It is...

the data's covariance matrix. Thus, the principal components are often computed by eigendecomposition of the data covariance matrix or singular value decomposition...

one wants to find the "nearest" correlation matrix to an "approximate" correlation matrix (e.g., a matrix which typically lacks semi-definite positiveness...

second step interprets this sequence as a Lehmer code or (almost equivalently) as an inversion table. In the Lehmer code for a permutation σ, the number dn...

matrix is a Hermitian matrix for complex random vectors and a symmetric matrix for real random vectors.: p.190  The autocorrelation matrix is a positive semidefinite...

of length k. (Equivalently, this vector might be described as a (k × 1)-matrix.) The vector is modelled as a linear function of its previous value. The...

covariance matrix Σ, and let A be a matrix that can act on X {\displaystyle \mathbf {X} } on the left. The covariance matrix of the matrix-vector product...

In statistics, sometimes the covariance matrix of a multivariate random variable is not known but has to be estimated. Estimation of covariance matrices...

generalized Riemann hypothesis, as several of its "predictions" are true. Lehmer's phenomenon, where two zeros are sometimes very close, is sometimes given...

that either of two different conjectures would imply that the exponent of matrix multiplication is 2. Algorithms for computing transforms of functions (particularly...

(also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the multivariate frequency distribution of the variables...

generator is often called a multiplicative congruential generator (MCG), or Lehmer RNG. If c ≠ 0, the method is called a mixed congruential generator.: 4- ...

observations. While there is no perfect way of describing the confusion matrix of true and false positives and negatives by a single number, the Matthews...

{\displaystyle 1\leq j\leq k} . The inverse of the covariance matrix is called the precision matrix, denoted by Q = Σ − 1 {\displaystyle {\boldsymbol {Q}}={\boldsymbol...

"approximate numbers", the second of which forms a real algebra. D. H. Lehmer reviewed the article in Mathematical Reviews and observed that this second...

3342336 ≈ 7.09. {\displaystyle {\tfrac {118518239}{3342336}}\approx 7.09.} Lehmer (1940) showed that the maximum value (Mn) of B n ( x ) {\displaystyle B_{n}(x)}...

positive semi-definite square matrix, commonly referred to as the variance-covariance matrix (or simply as the covariance matrix). If X {\displaystyle X} is...

closely their distribution approximates the shape of the GUE random matrix. Lehmer pair Goldston, D. A.; Montgomery, H. L. (1987). "Pair correlation of...

algorithm has been developed incrementally starting in 1870 by Ernst Meissel, Lehmer, Lagarias-Miller-Odlyzko, and Deléglise-Rivat that computes isolated values...

of −+1⁄2 represents the matrix square root of the inverse of a matrix. The correlation matrix of T will be the identity matrix. If a new data observation...

the Euclidean algorithm can be collected in a 2-by-2 matrix of single-word integers. When Lehmer's algorithm encounters a quotient that is too large, it...

linear function of a matrix M is a linear combination of its elements (with given coefficients), M ↦ tr(AM) where A is the matrix of the coefficients;...