robust models in probability sampling in the estimation of a population mean or total from a random sample certain methods based on linear models are known to be automatically design consistent regardless of how well the underlying model describes the population a sufficient condition is identified for this type of robustness to model failure the condition which we call internal bias calibration relates to the combination of a model and the method used to fit it included among the internally bias calibrated models in addition to the aforementioned linear models are certain canonical link generalized linear models and nonparametric regressions constructed from them by a particular style of local likelihood fitting other models can often be made robust by using a suboptimal fitting method thus the class of model based but design consistent analyses is enlarged to include more realistic models for certain types of survey variable such as binary indicators and counts particular applications discussed are the estimation of the size of a population subdomain as arises in tax auditing for example and the estimation of a bootstrap tail probability

contribution of leaky modes in the modal analysis of unbounded problems with perfectly matched layers the modal analysis of wave problems of unbounded type involves a continuous sum of radiation modes this continuum is difficult to handle mathematically and physically it can be approximated by a discrete set of leaky modes corresponding to improper modes growing to infinity perfectly matched layers pmls have been widely applied in numerical methods to efficiently simulate infinite media most often without considering a modal approach this letter aims to bring insight into the modal basis computed with pmls pmls actually enable to reveal of the contribution of leaky modes by redefining the continua two for elastodynamics discretized after pml truncation

a mixed finite element method for the arches assembly problem abstract we consider a loaded arches assembly problem with a common thickness to approximate the solution of this problem we consider the geometry of the global structure as the limit of a sequence of regular functions thereafter we approach each component of the sequence by its interpolant function an augmented discrete mixed finite element method which takes into account an approximation of the geometry is then formulated in order to give a suitable approximation of the solution

a krylov stability corrected coordinate stretching method to simulate wave propagation in unbounded domains the krylov subspace projection approach is a well established tool for the reducedorder modeling of dynamical systems in the time domain in this paper we address the main issues obstructing the application of this powerful approach to the time domain solution of exterior wave problems we use frequency independent perfectly matched layers to simulate the extension to infinity pure imaginary stretching functions based on zolotarev s optimal rational approximation of the square root are implemented leading to perfectly matched layers with a controlled accuracy over a complete spectral interval of interest a new krylov based solution method via stabilitycorrected operator exponents is presented which allows us to construct reduced order models roms that respect the delicate spectral properties of the original scattering problem the roms are unconditionally stable and are based on a renormalized bi lanczos algorithm we give a theoretical foundation of our method and illustrate its performance through a number of numerical examples in which we simulate two dimensional electromagnetic wave propagation in unbounded domains including a photonic waveguide example the new algorithm outperforms the conventional finitedifference time domain method for problems on large time intervals

a new class of mixed finite element methods for reissner mindlin plates a new class of finite elements for the reissner mindlin plate problem is presented the family is based on a modified mixed formulation recently introduced by arnold and brezzi boundary value problems for partial differential equations and applications j l lions and c baiocchi eds masson paris 1993 a result of stability and convergence uniformly in the thickness is provided

estimation of distribution functions and medians under sampling with unequal probabilities summary we consider sampling with probability proportional to size or aggregate size and derive a number of estimators of the finite population distribution function the estimators are compared theoretically and empirically by inverting the distribution function estimators we obtain estimators of the finite population median the performance of these median estimators are investigated

an efficient perfectly matched layer based multilevel fast multipole algorithm for large planar microwave structures an efficient multilevel fast multipole algorithm mlfma formalism to model radiation and scattering by from large planar microwave structures is presented the technique relies on an electric field integral equation efie formulation and a series expansion for the green dyadic based on the use of perfectly matched layers pml in this way a new pml mlfma is developed to efficiently evaluate matrix vector multiplications arising in the iterative solution of the scattering problem the computational complexity of the new algorithm scales down to o n for electrically large structures the theory is validated by means of several illustrative numerical examples

discretization of continuous spectra based on perfectly matched layers as a tool of analysis in physics wavefields are often expanded in a set of eigensolutions obtained from a sturm liouville problem for singular sturm liouville problems subject to radiation boundary conditions i e problems defined on an infinite domain this set of eigensolutions has continuous parts in this paper we will show that it is possible to approximate this continuous set of eigensolutions by a discrete set of eigensolutions of the same sturm liouville operator but subject to dirichlet boundary conditions in complex space the idea of dirichlet boundary conditions in complex space stems from the perfectly matched layer pml absorbing boundary condition the pml was introduced in 1994 j p berenger j comput phys 114 1994 pp 185 200 as an absorbing termination of a finite difference time domain grid these complex space dirichlet boundary conditions have been used recently to close open electromagnetic waveguide structures in the present paper we aim at developing a mathemati

bias robust estimation in finite populations using nonparametric calibration a standard problem in sample survey inference is that of predicting the finite population total h of a function h y of a random variable y the model based approach to this problem first defines a working model for y and then predicts h by estimating its expectation under conditional on the sample values of y this approach leads to biased predictions if is incorrect we explore an automatic solution to this misspecification bias that uses nonparametric regression to define a robust but inefficient predictor of h and then calibrates this predictor for its bias under an application to prediction of the finite population distribution function of a population of australian beef farms is presented

series representation of green dyadics for layered media using pmls the green dyadics for closed layered media i e layered media bounded by a perfectly conducting plate at the bottom and top of the structure can be expanded in a discrete surface wave series for open layered media with semi infinite layers at the top and or bottom of the structure the discrete series needs to be complemented by a branch cut integral of space waves in this paper we present a technique to circumvent this branch cut integral by truncating the semi infinite layers with a perfectly matched layer pml that is backed by a perfect electric conductor pec it is demonstrated that in this way it is possible to obtain an accurate series or closed form representation for the green dyadic of the open layered medium the series allows a very efficient calculation and storage of the green dyadic if it is needed for multiple observation and or excitation points very close to the source the series loses efficiency it is shown that the determination of the surface waves in the pml truncated layered medium has the same complexity as the determination of the surface waves in a pec truncated layered medium without a pml

on estimating distribution functions and quantiles from survey data using auxiliary information summary ratio and difference estimators of a population distribution function under a general sampling design are obtained using auxiliary population information the relative mean errors and relative mean square errors of these estimators and a model based estimator of chambers dunstan 1986 are compared through a simulation study the advantages of the design based estimators over the model based estimator under model misspecifications especially for large samples are demonstrated ratio and difference estimators of a population quantile are also studied

a perfectly matched layer for fluid solid problems application to ocean acoustics simulations with solid ocean bottoms a time domain legendre spectral element method is described for full wave simulation of ocean acoustics models i e coupled fluid solid problems in unbounded or semi infinite domains taking into account shear wave propagation in the ocean bottom the technique can accommodate range dependent and depth dependent wave speed and density as well as steep ocean floor topography for truncation of the infinite domain to efficiently absorb outgoing waves a fluid solid complex frequency shifted unsplit perfectly matched layer is introduced based on the complex coordinate stretching technique the complex stretching is rigorously taken into account in the derivation of the fluid solid matching condition inside the absorbing layer which has never been done before in the time domain two implementations are designed a convolutional formulation and an auxiliary differential equation formulation because the latter allows for implementation of high order time schemes leading to reduced numerical dispersion and dissipation a topic of importance in particular in long range ocean acoustics simulations the method is validated for a two dimensional fluid solid pekeris waveguide and for a three dimensional seamount model which shows that the technique is accurate and numerically long time stable compared with widely used paraxial absorbing boundary conditions the perfectly matched layer is significantly more efficient at absorbing both body waves and interface waves

an evaluation of model dependent and probability sampling inferences in sample surveys abstract in this paper we are concerned with inferences from a sample survey to a finite population we contrast inferences that are dependent on an assumed model with inferences based on the randomization induced by the sample selection plan randomization consistency for finite population estimators is defined and adopted as a requirement of probability sampling a numerical example is examined to illustrate the dangers in the use of model dependent estimators even when the model is apparently consonant with the sample data the paper concludes with a summary of principles that we believe should guide the practitioner of sample surveys of finite populations

error control in the perfectly matched layer based multilevel fast multipole algorithm the development of efficient algorithms to analyze complex electromagnetic structures is of topical interest application of these algorithms in commercial solvers requires rigorous error controllability in this paper we focus on the perfectly matched layer based multilevel fast multipole algorithm pml mlfma a dedicated technique constructed to efficiently analyze large planar structures more specifically the crux of the algorithm viz the pertinent layered medium green functions is under investigation therefore particular attention is paid to the plane wave decomposition for 2 d homogeneous space green functions in very lossy media as needed in the pml mlfma the result of the investigations is twofold first upper bounds expressing the required number of samples in the plane wave decomposition as a function of a preset accuracy are rigorously derived these formulas can be used in 2 d homogeneous lossy media mlfmas second a more heuristic approach to control the error of the pml mlfma s green functions is presented the theory is verified by means of several numerical experiments

on the completeness of eigenmodes in a parallel plate waveguide with a perfectly matched layer termination an explicit proof of the completeness of the eigenmodes of a grounded parallel plate waveguide with a perfectly matched layer pml termination is given the proof is based on a general theorem governing the completeness of sets of complex exponentials the green s function of the structure is then obtained by means of a biorthogonalization procedure a comparison with the green s function of a grounded halfspace indicates that a pml termination simulates the open halfspace efficiently index terms completeness eigenmodes green s function parallel plate waveguide perfectly matched layer pml

a uniformly accurate finite element method for the reissner mindlin plate a simple finite element method for the reissner mindlin plate model in the prim itive variables is presented and analyzed the method uses nonconforming linear finite elements for the transverse displacement and conforming linear finite elements enriched by bubbles for the rotation with the computation of the element stiffness matrix modified by the inclusion of a simple elementwise averaging it is proved that the method converges with optimal order uniformly with respect to thickness

scattering and radiation from by 1 d periodic metallizations residing in layered media an efficient technique is proposed to compute the scattering or radiation from by 1 d periodic structures residing in a layered background medium the technique is based on a mixed potential integral equation mpie combined with the method of moments mom solving for the unknown current density flowing within a unit cell of the periodic structure the formalism requires the knowledge of the pertinent layered medium green s functions with 1 d periodicity here these green s functions are derived in closed form by invoking the perfectly matched layer pml paradigm the stationary phase method is applied to determine the far field of the infinite periodic structure leading to a series of floquet modes in addition approximating this series leads to an efficient technique to estimate the scattering or radiation from by large but finite periodic structures with a 1 d periodic character the theory is illustrated and validated by means of various examples stemming from scattering and radiation applications from by antenna arrays residing on microstrip substrates the efficiency of the method is also demonstrated

convergence of mixed finite element approximations for the shallow arch problem the stability and convergence of mixed finite element methods are investigated for an equilibrium problem for thin shallow elastic arches the problem in its standard form contains two terms corresponding to the contributions from the shear and axial strains with a small parameter lagrange multipliers are introduced to formulate the problem in an alternative mixed form questions of existence and uniqueness of solutions to the standard and mixed problems are addressed it is shown that finite element approximations of the mixed problem are stable and convergent reduced integration formulations are equivalent to a mixed formulation which in general is distinct from the formulation shown to be stable and convergent except when the order of polynomial interpolationt of the arch shape satisfies 1 t min 2 r wherer is the order of polynomial approximation of the unknown variables

robust estimation for finite populations based on a working model a common scenario in finite population inference is that it is possible to find a working superpopulation model which explains the main features of the population but which may not capture all the fine details in addition there are often outliers in the population which do not follow the assumed superpopulation model in situations like these it is still advantageous to make use of the working model to estimate finite population quantities provided that we do it in a robust manner the approach that we suggest is first to fit the working model to the sample and then to fine tune for departures from the model assumed by estimating the conditional distribution of the residuals as a function of the auxiliary variable this is a more direct approach to handling outliers and model misspecification than the huber approach that is currently being used two simple methods stratification and nearest neighbour smoothing are used to estimate the conditional distributions of the residuals which result in two modifications to the standard model based estimator of the population distribution function the estimators suggested perform very well in simulation studies involving two types of model departure and have small variances due to their model based construction as well as acceptable bias the potential advantage of the proposed robustified model based approach over direct nonparametric regression is also demonstrated

computation and storage of the bianisotropic scalar green s function and its derivatives a set of algorithms is proposed for the accurate and efficient computation and storage of the bianisotropic scalar green s function the computation is based on an expansion of the green s function into chebyshev polynomials the analytical properties of these polynomials are exploited to allow the accurate computation of the derivatives of the green s function as well as the green s function itself for lossy materials the proposed computation strategy is provably robust in addition a multilevel storage scheme with a favorable complexity based on the chebyshev polynomial expansion is proposed for the storage of the expansion coefficients numerical results showcase the accuracy and computational complexity of the proposed algorithms

outlier robust finite population estimation abstract outliers in sample data are a perennial problem for applied survey statisticians moreover it is a problem for which traditional sample survey theory offers no real solution beyond the sensible advice that such sample elements should not be weighted to their fullest extent in estimation sample outliers can be identified as of two basic types here we are concerned with the first type which may conveniently be termed representative outliers these are sample elements with values that have been correctly recorded and that cannot be assumed to be unique that is there is no good reason to assume there are no more similar outliers in the nonsampled part of the target population the remaining sample outliers which by default are termed nonrepresentative are sample elements whose data values are incorrect or unique in some sense methods for dealing with these nonrepresentative outliers lie basically within the scope of survey editing and imputation theory and are therefore not considered in

local linear quantile regression abstract in this article we study nonparametric regression quantile estimation by kernel weighted local linear fitting two such estimators are considered one is based on localizing the characterization of a regression quantile as the minimizer of e pp y a x x where p is the appropriate check function the other follows by inverting a local linear conditional distribution estimator and involves two smoothing parameters rather than one our aim is to present fully operational versions of both approaches and to show that each works quite well although either might be used in practice we have a particular preference for the second our automatic smoothing parameter selection method is novel the main regression quantile smoothing parameters are chosen by rule of thumb adaptations of state of the art methods for smoothing parameter selection for regression mean estimation the techniques are illustrated by application to two datasets and compared in simulations

bias calibrated estimation from sample surveys containing outliers we discuss the problem of estimating finite population parameters on the basis of a sample containing representative outliers we clarify the motivation for chambers s bias calibrated estimator of the population total and show that bias calibration is a key idea in constructing estimators of finite population parameters we then link the problem of estimating the population total to distribution function or quantile estimation and explore a methodology based on the use of chambers s estimator we also propose methodology based on the use of robust estimates and a bias calibrated form of the chambers and dunstan estimator of the population distribution function this proposal leads to a bias calibrated estimator of the population total which is an alternative to that of chambers we present a small simulation study to illustrate the utility of these estimators

a high performance upgrade of the perfectly matched layer multilevel fast multipole algorithm for large planar microwave structures an improvement of the perfectly matched layer multilevel fast multipole algorithm pml mlfma for simulating large planar microwave structures is presented by exploiting the low rank property of the pml mlfma multimodal aggregation and disaggregation matrices considerable reductions in memory usage and computation time are obtained the method has been extensively validated demonstrating complete error controllability when simulating large planar microwave structures reductions in memory requirements and cpu time of more than 60 and 40 have been achieved

efficient and doubly robust imputation for covariate dependent missing responses in this article we study a well known response missing data problem missing data is an ubiquitous problem in medical and social science studies imputation is one of the most popular methods for dealing with missing data the most commonly used imputation that makes use of covariates is regression imputation in which the regression model can be parametric semiparametric or nonparametric parametric regression imputation is efficient but is not robust against misspecification of the regression model although nonparametric regression imputation such as nearest neighbor imputation and kernel regression imputation is model free it is not efficient especially if the dimension of covariate vector is high the well known problem of curse of dimensionality semiparametric regression imputation such as partially linear regression imputation can reduce the dimension of the covariate in nonparametric regression fitting but is not robust against misspecification of the linear component in the regression

accuracy of some finite element models for arch problems abstract this paper presents a theoretical accuracy study of some finite element models for thin arches as is well known the selection of finite elements for curved members is quite a delicate problem we obtain order estimates of errors of finite element solutions by means of the perturbation theory of mixed models and the technique of asymptotic expansion in particular we theoretically show that certain finite element models may suffer from the so called locking phenomenon numerical results are also given to be compared with the theoretical error estimates

extrapolation methods for sommerfeld integral tails a review is presented of the extrapolation methods for accelerating the convergence of sommerfeld type integrals i e semi infinite range integrals with bessel function kernels which arise in problems involving antennas or scatterers embedded in planar multilayered media attention is limited to partition extrapolation procedures in which the sommerfeld integral is evaluated as a sum of a series of partial integrals over finite subintervals and is accelerated by an extrapolation method applied over the real axis tail segment spl alpha spl infin of the integration path where spl alpha 0 is selected to ensure that the integrand is well behaved an analytical form of the asymptotic truncation error or the remainder which characterizes the convergence properties of the sequence of partial sums and serves as a basis for some of the most efficient extrapolation methods is derived several extrapolation algorithms deemed to be the most suitable for the sommerfeld integrals are described and their performance is compared it is demonstrated that the performance of these methods is strongly affected by the horizontal displacement of the source and field points spl rho and by the choice of the subinterval break points furthermore it is found that some well known extrapolation techniques may fail for a number of values of spl rho and ways to remedy this are suggested finally the most effective extrapolation methods for accelerating sommerfeld integral tails are recommended

field decomposition and factorization of the helmholtz determinant operator for bianisotropic media the paper generalizes the class of media for which the electromagnetic em fields can be decomposed in two independent components each of the two components see the medium as a simpler so called equivalent medium this generalization was possible because it was realized that the plane wave fields satisfy e spl middot d h spl middot b 0 this discovery allows us to come to a consistent structure for the class of decomposable and factorizable bianisotropic media encompassing all previously studied media as special cases the class of media of the present paper is shown to be closed with respect to duality transformations we dare to say that the present paper puts the crown on a long quest for always more general classes of media that allow decomposition and factorization the equivalent media yield a new class of media that allow a closed form representation of the green dyadics

estimating distribution functions from survey data summary a simple method for estimating population distribution functions and associated quantiles from sample survey data is described and some asymptotic theory for it presented the method assumes a model based approach to survey estimation and allows auxiliary population information to be directly incorporated into the estimation process monte carlo results comparing the proposed method with conventional design based methods are given these suggest that the model based approach offers significant gains when the auxiliary population information is linearly related to the survey variables of interest

methods for estimating a conditional distribution function abstract motivated by the problem of setting prediction intervals in time series analysis we suggest two new methods for conditional distribution estimation the first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density estimation it produces distribution estimators that may be of arbitrarily high order but nevertheless always lie between 0 and 1 the second method involves an adjusted form of the nadaraya watson estimator it preserves the bias and variance properties of a class of second order estimators introduced by yu and jones but has the added advantage of always being a distribution itself our methods also have application outside the time series setting for example to quantile estimation for independent data this problem motivated the work of yu and jones

approximation of general arch problems by straight beam elements in this paper we approximate the solution of a problem of a general arch by a nonconforming method using straight beam elements and taking into account numerical integration compatibility conditions which have to be satisfied at the mesh points are given these conditions ensure for this method the same order of convergence as usual conforming finite element methods

median estimation in the presence of auxiliary information summary this paper deals with the estimation under simple random sampling of a finite population median in the presence of an auxiliary variable an estimator which is a simple modification of the ratio estimator for the mean is studied along with two other proposed estimators derived from a different approach these estimators are applicable in situations where only the population median or a grouped frequency distribution of the auxiliary variable is known on the basis of the asymptotic properties derived and some simulation results the efficiencies of these estimators are compared it is shown that the two estimators proposed unlike that obtained from modifying the ratio estimator always dominate the sample median in mean squared error and that their efficiencies depend directly on the probability of concordance rather than on the validity of a linearity assumption between the survey variable and the auxiliary variable when the linearity assumption is approximately satisfied the three estimators are seen to have comparable efficiencies while the modified ratio estimator is found to be quite sensitive to departures from the linearity assumnption