Sequential fixed accuracy estimation for nonstationary autoregressive processes

For an autoregressive process of order p, the paper proposes new sequential estimates for the unknown parameters based on the least squares (LS) method. The sequential estimates use p stopping rules for collecting the data and presumes a special modification the sample Fisher information matrix in the LS estimates. In case of Gaussian disturbances, the proposed estimates have non-asymptotic normal joint distribution for any values of unknown autoregressive parameters. It is shown that in the i.i.d. case with unspecified error distributions, the new estimates have the property of uniform asymptotic normality for unstable autoregressive processes under some general condition on the parameters. Examples of unstable autoregressive models satisfying this condition are considered.

     

Prediction of multivariate time series by autoregressive model fitting

Suppose the stationary r-dimensional multivariate time series {y_t} is generated by an infinite autoregression. For lead times h≥1, the linear prediction of y_t+h based on y_t, y_t−1,… is considered using an autoregressive model of finite order k fitted to a realization of length T. Assuming that k → ∞ (at some rate) as T → ∞, the consistency and asymptotic normality of the estimated autoregressive coefficients are derived, and an asymptotic approximation to the mean square prediction error based on this autoregressive model fitting approach is obtained. The asymptotic effect of estimating autoregressive parameters is found to inflate the minimum mean square prediction error by a factor of (1 + kr/T).     

Algebraic convergence for anisotropic edge elements in polyhedral domains

We study approximation errors for the h-version of Nédélec edge elements on anisotropically refined meshes in polyhedra. Both tetrahedral and hexahedral elements are considered, and the emphasis is on obtaining optimal convergence rates in the H(curl) norm for higher order elements. Two types of estimates are presented: First, interpolation error estimates for functions in anisotropic weighted Sobolev spaces. Here we consider not only the H(curl)-conforming Nédélec elements, but also the H(div)-conforming Raviart-Thomas elements which appear naturally in the discrete version of the de Rham complex. Our technique is to transport error estimates from the reference element to the physical element via highly anisotropic coordinate transformations. Second, Galerkin error estimates for the standard H(curl) approximation of time harmonic Maxwell equations. Here we use the anisotropic weighted Sobolev regularity of the solution on domains with three-dimensional edges and corners. We also prove the discrete compactness property needed for the convergence of the Maxwell eigenvalue problem. Our results generalize those of [40] to the case of polyhedral corners and higher order elements.     

The inverse partial correlation function of a time series and its applications

The concept of the inverse correlation function of a stationary process was introduced by Cleveland (Technometrics14 (1972), 277–293). The inverse partial correlation function of a stationary process may intuitively be thought of as the corresponding extension of the concept of the partial correlation function. A precise mathematical definition of this function is given. Its importance in describing the structure of a moving average of finite order h is discussed. Having observed X₁,…,X_T, the autoregressive method of estimating the inverse correlations is employed for constructing sample estimates of the inverse partial correlations. For the hth-order moving average process, the estimates beyond h are, as T → ∞, asymptotically independent normally distributed with 0 mean and variance T^?1. Their use for estimating h and for testing hypotheses concerning h is examined.     

A second order nonconforming rectangular finite element method for approximating Maxwell’s equations

The main objective of this paper is to present a new rectangular nonconforming finite element scheme with the second order convergence behavior for approximation of Maxwell’s equations.Then the corresponding optimal error estimates are derived.The difficulty in construction of this finite element scheme is how to choose a compatible pair of degrees of freedom and shape function space so as to make the consistency error due to the nonconformity of the element being of order O(h 3 ) ,properly one order higher than that of its interpolation error O(h 2 ) in the broken energy norm,where h is the subdivision parameter tending to zero.     

On identification of the threshold diffusion processes

We consider the problems of parameter estimation for several models of threshold ergodic diffusion processes in the asymptotics of large samples. These models are the direct continuous time analogues of the well known in time series analysis threshold autoregressive models. In such models, the trend is switching when the observed process attaints some (unknown) values and the problem is to estimate it or to test some hypotheses concerning these values. The related statistical problems correspond to the singular estimation or testing, for example, the rate of convergence of estimators is T and not ?T{\sqrt{T}} as in regular estimation problems. We study the asymptotic behavior of the maximum likelihood and Bayesian estimators and discuss the possibility of the construction of the goodness-of-fit test for such models of observation.     

Eigen-oscillations of contrasting non-homogeneous elastic bodies: asymptotic and uniform estimates for eigenvalues

Estimates of convergence rates for the eigenvalues of spectralstiff elasticity problems are obtained. The bounds in the estimatesare expressed in terms of the stiffness ratio h and characteristicproperties of the limit spectrum for low and middle frequencyranges. These estimates allow us to distinguish between individualand collective asymptotics of the eigenvalues and eigenvectorsand to determine precisely the intervals for the small parameterh where the mathematical model considered provides a suitableapproach and accuracy. The results in this paper hold for differentboundary conditions, two- and three-dimensional models and scalarproblems.     

An Optimal p-Refinement Strategy for Dynamic Iteration of Ordinary and Differential Algebraic Equations

Multiphysical simulation tasks are often numerically solved by dynamic iteration schemes. Usually, this demands the efficient and stable coupling of existing simulation software for the contributing physical subdomains or subsystem. Since the coupling is weakened by such a simulation strategy, iteration is needed to enhance the quality of the numerical approximation. By the means of error recursions, one obtains estimates for the approximation order and the reduction of error per iteration (convergence rate). It is know that the first iterations can be coarsely sampled (in time), but the last iterations need to be refined (h-refinement) to obtain the accuracy gain of latter iterations (‘sweeps’). In this work we discuss an optimal choice of the approximation order p used in the time integration with respect to the iteration ‘sweep’ count. It is deduced from the analytical error recursion and yields a p-refinement strategy. Numerical experiments show that our estimates are sharp and give a precise prediction of the correct convergence. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Weighted estimate for the convergence rate of a projection difference scheme for a parabolic equation and its application to the approximation of the initial-data control problem

A new technique is proposed for analyzing the convergence of a projection difference scheme as applied to the initial value problem for a linear parabolic operator-differential equation. The technique is based on discrete analogues of weighted estimates reflecting the smoothing property of solutions to the differential problem for t > 0. Under certain conditions on the right-hand side, a new convergence rate estimate of order O($ \sqrt \tau $ \sqrt \tau + h) is obtained in a weighted energy norm without making any a priori assumptions on the additional smoothness of weak solutions. The technique leads to a natural projection difference approximation of the problem of controlling nonsmooth initial data. The convergence rate estimate obtained for the approximating control problems is of the same order O($ \sqrt \tau $ \sqrt \tau + h) as for the projection difference scheme.     

Nonparametric high resolution spectral estimation

Summary The uniform rate of convergence of the integrated relative mean square error over a (with the sample sizeT) increasing classI _T of stationary processes is studied for several estimates of the spectral density. The classI _T is chosen in a way such that estimates with a good uniform rate of convergence overI _T may be termed high resolution spectral estimates. By using this criterion several effects are explained theoretically, for example the leakage effect. The advantages uf using data tapers are proved and the use of local and global bandwiths are studied. Furthermore, the behaviors of segment estimates are studied. Simulations are presented for the illustration of some effects.This work has been supported by the Deutsche Forschungsgemeinschaft     

Estimates of solutions of two-point problems for systems of first-order ordinary differential equations and the method of lines

In the paper estimates are established on the solution of systems of first-order differential equations subject to two-point conditions of the form which enable us, in particular, to obtain an estimate of the order of uniform convergence of the method of lines for solving periodic boundary-value problems for second-order nonlinear parabolic partial differential equations of form For problems with boundary conditions containing the derivatives where the functions satisfy, in a small neighborhood of the solutionu(t,x) being examined of Eq. (3), the inequalities, for which the approximation is only of the first order relative to the net steph, the uniform convergence of the approximate solutions to the exact one is established to the second order relative toh.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 90, pp. 277–296, 1979.     

Error estimates for the combinedh andp versions of the finite element method

Summary In theh-version of the finite element method, convergence is achieved by refining the mesh while keeping the degree of the elements fixed. On the other hand, thep-version keeps the mesh fixed and increases the degree of the elements. In this paper, we prove estimates showing the simultaneous dependence of the order of approximation on both the element degrees and the mesh. In addition, it is shown that a proper design of the mesh and distribution of element degrees lead to a better than polynomial rate of convergence with respect to the number of degrees of freedom, even in the presence of corner singularities. Numerical results comparing theh-version,p-version, and combinedh-p-version for a one dimensional problem are presented.     

Approximation du spectre d'un operateur lineaire; application aux operateurs differentiels elliptiques non autoadjoints

To be computed, the eigenvalues of a closed linear operatorT in a Banach space are usually approximated by the eigenvalues ofT h, a linear operator approximatingT in a finite dimensional space (for example, finite difference method, Galerkin method),h is a parameter which tends to 0. This approximation is studied in [2]; stability ofT h implies the continuity of the spectrum ofT h, whenh tends to 0.We present here a new kind of sufficient condition. For that purpose, we disconnect the continuity of the spectrum ofT h into lower and upper semicontinuities. And we give two different criteria for these semi-continuities. Applications to the approximation of nonselfadjoint elliptic operators by finite difference schemes, are given.     

On approximating the solution of the non-stationary Stokes equations using the cell discretization algorithm

The cell discretization algorithm, a nonconforming extension of the finite element method, is used to obtain approximations to the velocity and pressure satisfying the nonstationary Stokes equations. Error estimates show convergence of the approximations. An implementation using polynomial bases is described that permits the use of the continuous approximations of the h–p finite element method and exactly satisfies the solenoidal requirement. We express the error estimates in terms of the diameter h of a cell and the degree p of the approximation on each cell. Results of an experiment with p10 are presented that confirm the theoretical estimates.     

Numerical study of the HP version of mixed discontinuous finite element methods for reaction‐diffusion problems: The 1D case

This article studies the stability and convergence of the hp version of the three families of mixed discontinuous finite element (MDFE) methods for the numerical solution of reaction‐diffusion problems. The focus of this article is on these problems for one space dimension. Error estimates are obtained explicitly in the grid size h, the polynomial degree p, and the solution regularity; arbitrary space grids and polynomial degree are allowed. These estimates are asymptotically optimal in both h and p for some of these methods. Extensive numerical results to show convergence rates in h and p of the MDFE methods are presented. Theoretical and numerical comparisons between the three families of MDFE methods are described. © 2003 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 19: 525–553, 2003     

Variational Principles and Sobolev-Type Estimates for Generalized Interpolation on a Riemannian Manifold

The purpose of this paper is to study certain variational principles and Sobolev-type estimates for the approximation order resulting from using strictly positive definite kernels to do generalized Hermite interpolation on a closed (i.e., no boundary), compact, connected, orientable, m -dimensional C ^∞ Riemannian manifold , with C ^∞ metric g _ij . The rate of approximation can be more fully analyzed with rates of approximation given in terms of Sobolev norms. Estimates on the rate of convergence for generalized Hermite and other distributional interpolants can be obtained in certain circumstances and, finally, the constants appearing in the approximation order inequalities are explicit. Our focus in this paper will be on approximation rates in the cases of the circle, other tori, and the 2 -sphere. April 10, 1996. Dates revised: March 26, 1997; August 26, 1997. Date accepted: September 12, 1997. Communicated by Ronald A. DeVore.     

Approximations of linear control problems with bang-bang solutions

We analyse the Euler discretization to a class of linear optimal control problems. First we show convergence of order h for the discrete approximation of the adjoint solution and the switching function, where h is the mesh size. Under the additional assumption that the optimal control has bang-bang structure we show that the discrete and the exact controls coincide except on a set of measure O(h). As a consequence, the discrete optimal control approximates the optimal control with order 1 w.r.t. the L ¹-norm and with order 1/2 w.r.t. the L ²-norm. An essential assumption is that the slopes of the switching function at its zeros are bounded away from zero which is in fact an inverse stability condition for these zeros. We also discuss higher order approximation methods based on the approximation of the adjoint solution and the switching function. Several numerical examples underline the results.     

Error analysis of finite element approximations of the stochastic Stokes equations

Numerical solutions of the stochastic Stokes equations driven by white noise perturbed forcing terms using finite element methods are considered. The discretization of the white noise and finite element approximation algorithms are studied. The rate of convergence of the finite element approximations is proved to be almost first order (h|ln h|) in two dimensions and one half order ( h^\frac12h^{\frac{1}{2}}) in three dimensions. Numerical results using the algorithms developed are also presented.     

On saturation effects in the Neumann boundary control of elliptic optimal control problems

A Neumann boundary control problem for a linear-quadratic elliptic optimal control problem in a polygonal domain is investigated. The main goal is to show an optimal approximation order for discretized problems after a postprocessing process. It turns out that two saturation processes occur: The regularity of the boundary data of the adjoint is limited if the largest angle of the polygon is at least 2π/3. Moreover, piecewise linear finite elements cannot guarantee the optimal order, if the largest angle of the polygon is greater than π/2. We will derive error estimates of order h ^α with α∈[1,2] depending on the largest angle and properties of the finite elements. Finally, numerical test illustrates the theoretical results.     

Adaptive estimates for autoregressive processes

Let {X _t :t=0, ±1, ±2, ...} be a stationaryrth order autoregressive process whose generating disturbances are independent identically distributed random variables with marginal distribution functionF. Adaptive estimates for the parameters of {X _t } are constructed from the observed portion of a sample path. The asymptotic efficiency of these estimates relative to the least squares estimates is greater than or equal to one for all regularF. The nature of the adaptive estimates encourages stable behavior for moderate sample sizes. A similar approach can be taken to estimation problems in the general linear model. This research was partially supported by National Science Foundation Grant GP-31091X. American Mathematical Society 1970 subject classification. Primary 62N10; Secondary 62G35. Key words and phrases: autoregressive process, adaptive estimates, robust estimates.