The scaling and modified squaring method for matrix functions related to the exponential

In recent years, there has been a resurgence in the construction and implementation of exponential integrators, which are numerical methods specifically designed for the numerical solution of spatially discretized semi-linear partial differential equations. Exponential integrators use the matrix exponential and related matrix functions within the formulation of the numerical method. The scaling and squaring method is the most widely used method for computing the matrix exponential. The aim of this paper is to discuss the efficient and accurate evaluation of the matrix exponential and related matrix functions using a scaling and modified squaring method.     

Averaging operators for exponential splittings

Averaging operations are considered in connection with exponential splitting methods. Toeplitz plus Hankel related matrices are resplit by applying appropriate averaging operators leading to a hierarchy of structured matrices. With the resulting parts, the option of using exponential splitting methods becomes available. A related, seemingly important group of unitary unipotents is looked at. Based on a formula due to Lenard, a very fast iterative method to find the nearest Toeplitz plus Hankel matrix in the Frobenius norm is devised.     

P-stable exponentially-fitted Obrechkoff methods of arbitrary order for second-order differential equations

We consider the construction of P-stable exponentially-fitted symmetric two-step Obrechkoff methods for solving second order differential equations related to an initial value problem. Our approach is based on two ideas: for the exponential fitting, we follow the ideas of Ixaru and Vanden Berghe; for the P-stability we introduce exponentially-fitted Padé approximants to the exponential function. By combining these two ideas, we are able to construct P-stable methods of arbitrary (even) order.     

Approximation of the linear combination of $\varphi$-functions using the block shift-and-invert Krylov subspace method

In this paper, we develop an algorithm in which the block shift-and-invert Krylov subspace method can be employed for approximating the linear combination of the matrix exponential and related exponential-type functions. Such evaluation plays a major role in a class of numerical methods known as exponential integrators. We derive a low-dimensional matrix exponential to approximate the objective function based on the block shift-and-invert Krylov subspace methods. We obtain the error expansion of the approximation, and show that the variants of its first term can be used as reliable a posteriori error estimates and correctors. Numerical experiments illustrate that the error estimates are efficient and the proposed algorithm is worthy of further study.     

Exponential Rosenbrock integrators for option pricing

In this paper, we are concerned with the time integration of differential equations modeling option pricing. In particular, we consider the Black-Scholes equation for American options. As an alternative to existing methods, we present exponential Rosenbrock integrators. These integrators require the evaluation of the exponential and related functions of the Jacobian matrix. The resulting methods have good stability properties. They are fully explicit and do not require the numerical solution of linear systems, in contrast to standard integrators. We have implemented some numerical experiments in Matlab showing the reliability of the new method.     

Comparison of software for computing the action of the matrix exponential

The implementation of exponential integrators requires the action of the matrix exponential and related functions of a possibly large matrix. There are various methods in the literature for carrying out this task. In this paper we describe a new implementation of a method based on interpolation at Leja points. We numerically compare this method with other codes from the literature. As we are interested in applications to exponential integrators we choose the test examples from spatial discretization of time dependent partial differential equations in two and three space dimensions. The test matrices thus have large eigenvalues and can be nonnormal.     

RD-Rational Approximations of the Matrix Exponential

Restricted Denominator (RD) rational approximations to the matrix exponential operator are constructed by interpolation in points related to Krylov subspaces associated to a rational transform of the particular matrix considered. Convergence analysis are provided. Numerical experiments show the effectiveness of the proposed methods in applications involving discretizations of differential operators.     

Efficient algorithmic implementation of the Voigt/complex error function based on exponential series approximation

We show that a Fourier expansion of the exponential multiplier yields an exponential series that can compute high-accuracy values of the complex error function in a rapid algorithm. Numerical error analysis and computational test reveal that with essentially higher accuracy it is as fast as FFT-based Weideman’s algorithm at a regular size of the input array and considerably faster at an extended size of the input array. As this exponential series approximation is based only on elementary functions, the algorithm can be implemented utilizing freely available functions from the standard libraries of most programming languages. Due to its simplicity, rapidness, high-accuracy and coverage of the entire complex plane, the algorithm is efficient and practically convenient in numerical methods related to the spectral line broadening and other applications requiring error-function evaluation over extended input arrays.     

Orthogonal polynomials,Padé approximations and A-stability

This paper consists of a brief survey of implicit Runge-Kutta methods based on Gauss-Legendre and closely related quadrature formulas, together with a new proof of a classical result. The classical result concerns the A-stability of those implicit Runge-Kutta methods whose stability functions are Padé approximations to the exponential function and lie on the diagonal and the first two subdiagonals of the Padé table.     

一个新的指数削减椭圆形分布族

A new family of univariate exponential slash distribution is introduced, which is based on elliptical distributions and defined by means of a stochastic representation as the scale mixture of an elliptically distributed random variable with respect to the power of an exponential random variable. The same idea is extended to the multivariate case. General properties of the resulting families, including their moments and kurtosis coefficient, are studied. And inferences based on methods of moment and maximum likelihood are discussed. A real data is presented to show this family is flexible and fits much better than other related families.     

Operator Identities and the Solution of Linear Matrix Difference and Differential Equations

We use operator identities in order to solve linear homogeneous matrix difference and differential equations and we obtain several explicit formulas for the exponential and for the powers of a matrix as an example of our methods. Using divided differences we find solutions of some scalar initial value problems and we show how the solution of matrix equations is related to polynomial interpolation.     

Implementation of exponential Rosenbrock-type integrators

In this paper, we present a variable step size implementation of exponential Rosenbrock-type methods of orders 2, 3 and 4. These integrators require the evaluation of exponential and related functions of the Jacobian matrix. To this aim, the Real Leja Points Method is used. It is shown that the properties of this method combine well with the particular requirements of Rosenbrock-type integrators. We verify our implementation with some numerical experiments in MATLAB, where we solve semilinear parabolic PDEs in one and two space dimensions. We further present some numerical experiments in FORTRAN, where we compare our method with other methods from literature. We find a great potential of our method for non-normal matrices. Such matrices typically arise in parabolic problems with large advection in combination with moderate diffusion and mildly stiff reactions.     

A family of Numerov-type exponentially fitted predictor-corrector methods for the numerical integration of the radial Schrödinger equation

A family of predictor-corrector exponential Numerov-type methods is developed for the numerical integration of the one-dimensional Schrödinger equation. The formula considered contains certain free parameters which allow it to be fitted automatically to exponential functions. The new methods are very simple and integrate more exponential functions than both the well-known fourth-order Numerov-type exponentially fitted methods and the sixth algebraic order Runge-Kutta-type methods. Numerical results also indicate that the new methods are much more accurate than the other exponentially fitted methods mentioned above.     

Symmetric and symplectic exponential integrators for nonlinear Hamiltonian systems

This letter studies symmetric and symplectic exponential integrators when applied to numerically computing nonlinear Hamiltonian systems. We first establish the symmetry and symplecticity conditions of exponential integrators and then show that these conditions are extensions of the symmetry and symplecticity conditions of Runge–Kutta methods. Based on these conditions, some symmetric and symplectic exponential integrators up to order four are derived. Two numerical experiments are carried out and the results demonstrate the remarkable numerical behaviour of the new exponential integrators in comparison with some symmetric and symplectic Runge–Kutta methods in the literature.     

Weak exponential stability of stochastic differential equations

In this paper we introduce weak exponential stability of stochastic differential equations. In particular, we introduce weak exponential stability in mean, weak exponential asymptotical stability in mean and weak uniform asymptotical stability in mean. We also derive some results related to the above concepts     

Multi-item sales forecasting with total and split exponential smoothing

Efficient supply chain management relies on accurate demand forecasting. Typically, forecasts are required at frequent intervals for many items. Forecasting methods suitable for this application are those that can be relied upon to produce robust and accurate predictions when implemented within an automated procedure. Exponential smoothing methods are a common choice. In this empirical case study paper, we evaluate a recently proposed seasonal exponential smoothing method that has previously been considered only for forecasting daily supermarket sales. We term this method ‘total and split’ exponential smoothing, and apply it to monthly sales data from a publishing company. The resulting forecasts are compared against a variety of methods, including several available in the software currently used by the company. Our results show total and split exponential smoothing outperforming the other methods considered. The results were also impressive for a method that trims outliers and then applies simple exponential smoothing.     

NA随机变量序列加权和的Chover型重对数律

利用NA随机变量的指数不等式,对于具有重尾分布的同分布的NA随机变量序列,得到了用积分检验来刻划其加权部分和的极限定理,作为推论还得到了Chover型重对数律.把这些结果应用到经典的可和方式,获得了相应的结果.这些结果推广了已知的一些结论.     

Integral conditions for exponential dichotomy: A nonlinear approach

We give new necessary and sufficient integral conditions for the existence of exponential dichotomy of skew-product flows. Our methods are based on the structure of the associated stable subspace and unstable subspace. We propose a nonlinear approach, extending the study of exponential stability in terms of integral conditions to the case of uniform exponential dichotomy. We apply the main results to the study of uniform exponential dichotomy of non-autonomous systems.     

Exponential time integration for fast finite element solutions of some financial engineering problems

We consider exponential time integration schemes for fast numerical pricing of European, American, barrier and butterfly options when the stock price follows a dynamics described by a jump-diffusion process. The resulting pricing equation which is in the form of a partial integro-differential equation is approximated in space using finite elements. Our methods require the computation of a single matrix exponential and we demonstrate using a wide range of numerical tests that the combination of exponential integrators and finite element discretisations with quadratic basis functions leads to highly accurate algorithms for cases when the jump magnitude is Gaussian. Comparison with other time-stepping methods are also carried out to illustrate the effectiveness of our methods.