Score tests for inverse Gaussian mixtures

The mixed inverse Gaussian given by Whitmore (biScand. J. Statist., 13 , 1986, 211–220) provides a convenient way for testing the goodness‐of‐fit of a pure inverse Gaussian distribution. The test is a one‐sided score test with the null hypothesis being the pure inverse Gaussian (i.e. the mixing parameter is zero) and the alternative a mixture. We devise a simple score test and study its finite sample properties. Monte Carlo results show that it compares favourably with the smooth test of Ducharme ( Test , 10 , 2001, 271‐290). In practical applications, when the pure inverse Gaussian distribution is rejected, one is interested in making inference about the general values of the mixing parameter. However, as it is well known that the inverse Gaussian mixture is a defective distribution; hence, the standard likelihood inference cannot be applied. We propose several alternatives and provide score tests for the mixing parameter. Finite sample properties of these tests are examined by Monte Carlo simulation. Copyright © 2010 John Wiley & Sons, Ltd.     

Legendre multiscaling functions for solving the one‐dimensional parabolic inverse problem

An inverse problem concerning diffusion equation with a source control parameter is investigated. The approximation of the problem is based on the Legendre multiscaling basis. The properties of Legendre multiscaling functions are first presented. These properties together with Galerkin method are then utilized to reduce the inverse problem to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the new technique. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009     

Fractional Normal Inverse Gaussian Process

Normal inverse Gaussian (NIG) process was introduced by Barndorff-Nielsen (Scand J Statist 24:1–13, 1997) by subordinating Brownian motion with drift to an inverse Gaussian process. Increments of NIG process are independent and are stationary. In this paper, we introduce dependence between the increments of NIG process, by subordinating fractional Brownian motion to an inverse Gaussian process and call it fractional normal inverse Gaussian (FNIG) process. The basic properties of this process are discussed. Its marginal distributions are scale mixtures of normal laws, infinitely divisible for the Hurst parameter 1/2 ≤ H < 1 and are heavy tailed. First order increments of the process are stationary and possess long-range dependence (LRD) property. It is shown that they have persistence of signs LRD property also. A generalization to an n-FNIG process is also discussed, which allows Hurst parameter H in the interval (n − 1, n). Possible applications to mathematical finance and hydraulics are also pointed out.     

An efficient method for solving an inverse problem for the Richards equation

A parameter identification problem for the hydraulic properties of porous media is considered. Numerically, this inverse problem is solved by minimizing an output least-squares functional. The unknown hydraulic properties which are nonlinear coefficients of a partial differential equation are approximated by spline functions. The identification is embedded into a multi-level algorithm and coupled with a linear sensitivity analysis to describe the ill-posedness of the inverse problem.     

A numerical method for solving an inverse thermoacoustic problem

In this paper, we consider an inverse problem of determining the initial condition of an initial boundary value problem for the wave equation with some additional information about solving a direct initial boundary value problem. The information is obtained from measurements at the boundary of the solution domain. The purpose of our paper is to construct a numerical algorithm for solving the inverse problem by an iterative method called a method of simple iteration (MSI) and to study the resolution quality of the inverse problem as a function of the number and location of measurement points. Three two-dimensional inverse problem formulations are considered. The results of our numerical calculations are presented. It is shown that the MSI decreases the objective functional at each iteration step. However, due to the ill-posedness of the inverse problem the difference between the exact and approximate solutions decreases up to some fixed number k _min, and then monotonically increases. This shows the regularizing properties of the MSI, and the iteration number can be considered a regularization parameter.     

A stochastic model for the direct and inverse problem of adhesive materials

This work deals with the generation of artificial data based on experimental data for adhesive materials and the application of this data to the inverse and the direct problem. In reality there are only a very limited number of experimental data available. Therefore, the prediction of material behaviour is difficult and a statistical analysis with a stochastic proved thesis is nearly impossible. In order to increase the number of tests a method of stochastic simulation based on time series analysis is applied. With artificial data an arbitrary number of data is available and the process of the parameter identification can be statistically analysed. Additionally, one example is shown, which adapts the analysed material parameter to the direct problem. The stochastic finite element method is used to take into account the distribution and deviation of the fracture strain. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Modified Landweber tterations in a multilevel setting applied to the determination of nonlinear material parameters in piezoelectricity

An efficient solution of the inverse problem of identifying nonlinear dependencies in hyperbolic systems of PDEs, here piezoelectric material parameter curves, is the aim of this work. The dominant material tensor entries in the coupled field equations which describe the electromechanical interplay are approximated by functions depending on the physical field quantities electric field or mechanical stress. In order to solve this nonlinear and ill-posed problem of parameter curve identification efficiently, modified Landweber iterations (steepest descent and minimal error) will be studied. A multilevel approach is expedient due to the discretization of the unknown parameter curves and high computational efforts solving the forward problem (transient, nonlinear FEM computations). Theoretical investigations concerning convergence and regularization properties of the methods in a multilevel scenario will be presented, along with numerical results from an example in piezoelectricity. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A computational determination of the Cowper–Symonds parameters from a single Taylor test

A novel technique for the dynamic characterization of metals from a single Taylor impact test is proposed. This computational characterization procedure is based on the formulation and solution of a first class inverse problem, in which the silhouette of the Taylor specimen’s final shape is expressed as a vector of its geometrical moments and used as input parameter. The inverse characterization problem is reduced to an optimization problem where the optimum material parameters for the Cowper–Symonds material model are determined. The optimization process is performed by a range adaptation real-coded genetic algorithm. Numerical example for the characterisation of 1018 steel is implemented and presented to validate the methodology presented in this paper. The effectiveness and simplicity of the proposed characterization procedure makes it an appropriate tool for the characterization of metals at high strain rates.     

Recovering differential pencils on compact graphs

We study boundary value problems on compact graphs without circles (i.e. on trees) for second-order ordinary differential equations with nonlinear dependence on the spectral parameter. We establish properties of the spectral characteristics and investigate the inverse spectral problem of recovering the coefficients of the differential equation from the so-called Weyl vector which is a generalization of the Weyl function (m-function) for the classical Sturm-Liouville operator. For this inverse problem we prove the uniqueness theorem and obtain a procedure for constructing the solution by the method of spectral mappings.     

Retrieving the time-dependent thermal conductivity of an orthotropic rectangular conductor

The aim of this paper is to determine the thermal properties of an orthotropic planar structure characterized by the thermal conductivity tensor in the coordinate system of the main directions (Oxy) being diagonal. In particular, we consider retrieving the time-dependent thermal conductivity components of an orthotropic rectangular conductor from nonlocal overspecified heat flux conditions. Since only boundary measurements are considered, this inverse formulation belongs to the desirable approach of non-destructive testing of materials. The unique solvability of this inverse coefficient problem is proved based on the Schauder fixed point theorem and the theory of Volterra integral equations of the second kind. Furthermore, the numerical reconstruction based on a nonlinear least-squares minimization is performed using the MATLAB optimization toolbox routine lsqnonlin. Numerical results are presented and discussed in order to illustrate the performance of the inversion for orthotropic parameter identification.     

SPSA for oil-parameter estimation and reservoir management

In this paper we implement and test the Simultaneous Perturbation Stochastic Approximation method (SPSA) in order to perform parameter estimation or history matching in reservoir simulation. The SPSA algorithm allows the determination of descent directions with very few forward model evaluations no matter the number of parameters. We test this approach for the estimation of transmissibilities for a single-phase flow problem in very heterogeneous environments. The global properties of SPSA allow the determination of reasonable good inverse solutions which is demonstrated through numerical experiments. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Inverse spectral problem for differential operator pencils on noncompact spatial networks

We study boundary value problems on noncompact cycle-free graphs (i.e., trees) for second-order ordinary differential equations with a nonlinear dependence on the spectral parameter. We establish properties of the spectrum and analyze the inverse problem of reconstructing the coefficients of a differential equation on the basis of the so-called Weyl functions. For this inverse problem, we prove a uniqueness theorem and obtain a procedure for constructing the solution by the method of spectral mapping.     

Inverse Scattering Problems for Sturm–Liouville Operators with Spectral Parameter Dependent on Boundary Conditions

In this paper, we consider the inverse scattering problem for the Sturm–Liouville operator on the half-line [0,∞) with Herglotz function of spectral parameter in the boundary condition. The scattering data of the problem is defined, and its properties are investigated. The main equation is obtained for the solution of the inverse problem and it is shown that the potential is uniquely recovered in terms of the scattering data.     

On the selection of parameters in Self Scaling Variable Metric Algorithms

This paper addresses the problem of selecting the parameter in a family of algorithms for unconstrained minimization known as Self Scaling Variable Metric (SSVM) Algorithms. This family, that has some very attractive properties, is based on a two parameter formula for updating the inverse Hessian approximation, in which the parameters can take any values between zero and one. Earlier results obtained for SSVM algorithms apply to the entire family and give no indication of how the choice of parameter may affect the algorithm's performance. In this paper, we examine empirically the effect of varying the parameters and relaxing the line-search. Theoretical consideration also leads to a switching tule for these parameters. Numerical results obtained for the SSVM algorithm indicate that with proper parameter selection it is superior to the DFP algorithm, particularly for high-dimensional problems.This paper was presented at the 8^th International Symposium on Mathematical Programming held at Stanford University, California, August 1973.     

On two different inverse form finding methods for hyperelastic and elastoplastic materials

This contribution focuses on two different developments of mechanical-computational methods for the optimal determination of the initial shape of formed functional components knowing the deformed configuration, the applied loads and the boundary conditions. The first method uses an inverse mechanical formulation and can be applied to materials with hyperelastic behaviors. For materials with elastoplastic properties this method is not advocated, without knowing the final plastic strains, due to the non uniqueness of the solution. The second method uses a shape optimization formulation in the sense of an inverse problem via successive iterations of the direct problem. For hyperelastic materials the inverse mechanical formulation is preferred for its velocity and the non exhibition of possible mesh distortions. In the shape optimization formulation mesh distortions can be avoided by an update of the reference configuration of the functional part. Both methods are using a formulation in the logarithmic strain space. A numerical example for materials with isotropic elastoplastic behaviors illustrates the shape optimization formulation. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

线性硬化材料中稳恒扩展裂纹尖端场的粘塑性解

采用弹粘塑性力学模型,对线性硬化材料中平面应变扩展裂纹尖端场进行了渐近分析．假设人工粘性系数与等效塑性应变率的幂次成反比,通过量级匹配表明应力和应变均具有幂奇异性,奇异性指数由粘性系数中等效塑性应变率的幂指数唯一确定．通过数值计算讨论了Ⅱ型动态扩展裂纹尖端场的分区构造随各材料参数的变化规律．结果表明裂尖场构造由硬化系数所控制而与粘性系数基本无关．弱硬化材料的二次塑性区可以忽略,而较强硬化材料的二次塑性区和二次弹性区对裂尖场均有重要影响．当裂纹扩展速度趋于零时,动态解趋于相应的准静态解;当硬化系数为零时便退化为HR(Hui-Riedel)解．     

General regularization schemes for signal detection in inverse problems

The authors discuss how general regularization schemes, in particular, linear regularization schemes and projection schemes, can be used to design tests for signal detection in statistical inverse problems. It is shown that such tests can attain the minimax separation rates when the regularization parameter is chosen appropriately. It is also shown how to modify these tests in order to obtain a test which adapts (up to a log log factor) to the unknown smoothness in the alternative. Moreover, the authors discuss how the so-called direct and indirect tests are related in terms of interpolation properties.     

Artificial neural network based inverse reliability analysis

An inverse reliability analysis is the problem to find design parameters corresponding to specified reliability levels expressed by reliability index or by theoretical failure probability. Design parameters can be deterministic or they can be associated to random variables described by statistical moments. The aim is to solve generally not only the single design parameter case but also the multiple parameter problems with given multiple reliability constraints. A new general approach of inverse reliability analysis is proposed. The inverse analysis is based on the coupling of a stochastic simulation of Monte Carlo type and an artificial neural network. A novelty of the approach is the utilization of the efficient small-sample simulation method Latin Hypercube Sampling used for the stochastic preparation of the training set. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Inverse scattering problem for Sturm–Liouville operator with nonlinear dependence on the spectral parameter in the boundary condition

The inverse problem of the scattering theory for Sturm–Liouville operator on the half line with boundary condition depending quadratic on the spectral parameter is considered. Scattering data are defined, some properties of the scattering data are examined, the main equation is obtained, solvability of the integral equation is proved and uniqueness of algorithm to the potential with given scattering data is studied. Copyright © 2010 John Wiley & Sons, Ltd.     

Meta-control of an interacting-particle algorithm for global optimization

A common issue for stochastic global optimization algorithms is how to set the parameters of the sampling distribution (e.g. temperature, mutation/cross-over rates, selection rate, etc.) so that the samplings converge to the optimum effectively and efficiently. We consider an interacting-particle algorithm and develop a meta-control methodology which analytically guides the inverse temperature parameter of the algorithm to achieve desired performance characteristics (e.g. quality of the final outcome, algorithm running time, etc.). The main aspect of our meta-control methodology is to formulate an optimal control problem where the fractional change in the inverse temperature parameter is the control variable. The objectives of the optimal control problem are set according to the desired behavior of the interacting-particle algorithm. The control problem considers particles’ average behavior, rather than treating the behavior of individual particles. The solution to the control problem provides feedback on the inverse temperature parameter of the algorithm.