An explicit expression for the Fisher information matrix of a multiple time series process

The principal result in this paper is concerned with the derivative of a vector with respect to a block vector or matrix. This is applied to the asymptotic Fisher information matrix (FIM) of a stationary vector autoregressive and moving average time series process (VARMA). Representations which can be used for computing the components of the FIM are then obtained. In a related paper [A. Klein, A generalization of Whittle’s formula for the information matrix of vector mixed time series, Linear Algebra Appl. 321 (2000) 197-208], the derivative is taken with respect to a vector. This is obtained by vectorizing the appropriate matrix products whereas in this paper the corresponding matrix products are left unchanged.     

The Bezoutian, state space realizations and Fisher’s information matrix of an ARMA process

In this paper we derive some properties of the Bezout matrix and relate the Fisher information matrix for a stationary ARMA process to the Bezoutian. Some properties are explained via realizations in state space form of the derivatives of the white noise process with respect to the parameters. A factorization of the Fisher information matrix as a product in factors which involve the Bezout matrix of the associated AR and MA polynomials is derived. From this factorization we can characterize singularity of the Fisher information matrix.     

Cayley transform and the Kronecker product of Hermitian matrices

We consider the conditions under which the Cayley transform of the Kronecker product of two Hermitian matrices can be again presented as a Kronecker product of two matrices and, if so, if it is a product of the Cayley transforms of the two Hermitian matrices. We also study the related question: given two matrices, which matrix under the Cayley transform yields the Kronecker product of their Cayley transforms.     

Triangular factors of Cauchy and Vandermonde matrices

Explicit formulas for triangular factors of Cauchy and Vandermonde matrices and their inverses in terms of entries of these matrices are presented.     

Equivalent conditions for noncentral generalized Laplacianness and independence of matrix quadratic forms

Let Y be an n×p multivariate normal random matrix with general covariance Σ_Y and W be a symmetric matrix. In the present article, the property that a matrix quadratic form Y^′WY is distributed as a difference of two independent (noncentral) Wishart random matrices is called the (noncentral) generalized Laplacianness (GL). Then a set of algebraic results are obtained which will give the necessary and sufficient conditions for the (noncentral) GL of a matrix quadratic form. Further, two extensions of Cochran’s theorem concerning the (noncentral) GL and independence of a family of matrix quadratic forms are developed.     

Pairs of matrices that preserve the value of a generalized matrix function on the set of the upper triangular matrices

Let H be a subgroup of the symmetric group of degree m and let χ be an irreducible character of H. In this paper we give conditions that characterize the pairs of matrices that leave invariant the value of a generalized matrix function associated with H and χ, on the set of the upper triangular matrices.     

A factorization of the symmetric Pascal matrix involving the Fibonacci matrix

In this short note, we give a factorization of the Pascal matrix. This result was apparently missed by Lee et al. [Some combinatorial identities via Fibonacci numbers, Discrete Appl. Math. 130 (2003) 527-534].     

Displacement structure approach to Chebyshev-Vandermonde and related matrices

In this paper we use the displacement structure concept to introduce a new class of matrices, designated asChebyshev-Vandermonde-like matrices, generalizing ordinary Chebyshev-Vandermonde matrices, studied earlier by different authors. Among other results the displacement structure approach allows us to give a nice explanation for the form of the Gohberg-Olshevsky formulas for the inverses of ordinary Chebyshev-Vandermonde matrices. Furthermore, the fact that the displacement structure is inherited by Schur complements leads to a fastO(n ²) implementation of Gaussian elimination withpartial pivoting for Chebyshev-Vandermonde-like matrices.     

Simultaneous solutions of Sylvester equations and idempotent matrices separating the joint spectrum

We investigate simultaneous solutions of the matrix Sylvester equations A_iX-XB_i=C_i,i=1,2,…,k, where {A₁,…,A_k} and {B₁,…,B_k} are k-tuples of commuting matrices of order m×m and p×p, respectively. We show that the matrix Sylvester equations have a unique solution X for every compatible k-tuple of m×p matrices {C₁,…,C_k} if and only if the joint spectra σ(A₁,…,A_k) and σ(B₁,…,B_k) are disjoint. We discuss the connection between the simultaneous solutions of Sylvester equations and related questions about idempotent matrices separating disjoint subsets of the joint spectrum, spectral mapping for the differences of commuting k-tuples, and a characterization of the joint spectrum via simultaneous solutions of systems of linear equations.     

Tensor properties of multilevel Toeplitz and related matrices

A general proposal is presented for fast algorithms for multilevel structured matrices. It is based on investigation of their tensor properties and develops the idea recently introduced by Kamm and Nagy in the block Toeplitz case. We show that tensor properties of multilevel Toeplitz matrices are related to separation of variables in the corresponding symbol, present analytical tools to study the latter, expose truncation algorithms preserving the structure, and report on some numerical results confirming advantages of the proposal.     

On disjoint range matrices

For a square complex matrix F and for F^∗ being its conjugate transpose, the class of matrices satisfying R(F)∩R(F^∗)={0}, where R(.) denotes range (column space) of a matrix argument, is investigated. Besides identifying a number of its properties, several functions of F, such as F+F^∗, (F:F^∗), FF^∗+F^∗F, and F-F^∗, are considered. Particular attention is paid to the Moore-Penrose inverses of those functions and projectors attributed to them. It is shown that some results scattered in the literature, whose complexity practically prevents them from being used to deal with real problems, can be replaced with much simpler expressions when the ranges of F and F^∗ are disjoint. Furthermore, as a by-product of the derived formulae, one obtains a variety of relevant facts concerning, for instance, rank and range.     

Groups acting on circulant matrices

Summary If a groupG permutes a setI, andM is a multiplicative abelian group, a representation ofG onM ^I is given by permutation of coordinates. TheG-module homomorphisms intoM ^I arise from exponential maps. This framework encompasses those systems of functional equations that characterize generalized hyperbolic functions.     

Symmetric polynomials, Pascal matrices, and Stirling matrices

We consider lower-triangular matrices consisting of symmetric polynomials, and we show how to factorize and invert them. Since binomial coefficients and Stirling numbers can be represented in terms of symmetric polynomials, these results contain factorizations and inverses of Pascal and Stirling matrices as special cases. This work generalizes that of several other authors on Pascal and Stirling matrices.     

Fisher information and matrix-valued valuations

All continuous and affinely contravariant matrix-valued valuations on the Sobolev space W1,2(Rn) are completely classified. It is shown that there is a unique such valuation. This valuation turns out to be the Fisher information matrix.     

Generalized Leibniz functional matrices and factorizations of some well-known matrices

In this paper, we introduce the generalized Leibniz functional matrices and study some algebraic properties of such matrices. To demonstrate applications of these properties, we derive several novel factorization forms of some well-known matrices, such as the complete symmetric polynomial matrix and the elementary symmetric polynomial matrix. In addition, by applying factorizations of the generalized Leibniz functional matrices, we redevelop the known results of factorizations of Stirling matrices of the first and second kind and the generalized Pascal matrix.     

Bounded distance preserving surjections in the projective geometry of matrices

We examine surjective maps which preserve a fixed bounded distance in both directions on some classical dual polar spaces.     

Fast state space algorithms for matrix Nehari and Nehari-Takagi interpolation problems

Numerical algorithms with complexityO(n ²) operations are proposed for solving matrix Nehari and Nehari-Takagi problems withn interpolation points. The algorithms are based on explicit formulas for the solutions and on theorems about cascade decomposition of rational matrix function given in a state space form. The method suggests also fast algorithms for LDU factorizations of structured matrices. The numerical behavior of the designed algorithms is studied for a wide set of examples.     

A Robertson-type uncertainty principle and quantum Fisher information

Let A₁,…,A_N be complex self-adjoint matrices and let ρ be a density matrix. The Robertson uncertainty principle

     

Instability indices for matrix polynomials

There is a well-established instability index theory for linear and quadratic matrix polynomials for which the coefficient matrices are Hermitian and skew-Hermitian. This theory relates the number of negative directions for the matrix coefficients which are Hermitian to the total number of unstable eigenvalues for the polynomial. Herein we extend the theory to ?-even matrix polynomials of any finite degree. In particular, unlike previously known cases we show that the instability index depends upon the size of the matrices when the degree of the polynomial is greater than two. We also consider Hermitian matrix polynomials, and derive an index which counts the number of eigenvalues with nonpositive imaginary part. The results are refined if we consider the Hermitian matrix polynomial to be a perturbation of a ?-even polynomials; however, this refinement requires additional assumptions on the matrix coefficients.