application of a fractional step method to incompressible navier stokes equations a numerical method for computing three dimensional time dependent incompressible flows is presented the method is based on a fractional step or time splitting scheme in conjunction with the approximate factorization technique it is shown that the use of velocity boundary conditions for the intermediate velocity field can lead to inconsistent numerical solutions appropriate boundary conditions for the intermediate velocity field are derived and tested numerical solutions for flows inside a driven cavity and over a backward facing step are presented and compared with experimental data and other numerical results

estimation in generalized mixed models regression models containing fixed and random effects may have a response variable which is not normally distributed the generalized mixed model includes both discrete and continuous response variables and is developed here for problems in which the regression variables enter linearly into the model best linear unbiased predictor methods are extended to maximum likelihood and residual maximum likelihood estimation procedures applications in modelling discrete response variables and in survival analysis are discussed

a score test for zero inflation in a poisson distribution when analyzing poisson count data sometimes a lot of zeros are observed when there are too many zeros a zero inflated poisson distribution can be used a score test is presented to test whether the number of zeros is too large for a poisson distribution to fit the data well

zero inflated poisson regression with an application to defects in manufacturing zero inflated poisson zip regression is a model for count data with excess zeros it assumes that with probability p the only possible observation is 0 and with probability 1 p a poisson random variable is observed for example when manufacturing equipment is properly aligned defects may be nearly impossible but when it is misaligned defects may occur according to a poisson distribution both the probability p of the perfect zero defect state and the mean number of defects in the imperfect state may depend on covariates sometimes p and are unrelated other times p is a simple function of such as p l 1 t for an unknown constant t in either case zip regression models are easy to fit the maximum likelihood estimates mle s are approximately normal in large samples and confidence intervals can be constructed by inverting likelihood ratio tests or using the approximate normality of the mle s simulations suggest that the confidence intervals based on likelihood ratio test

estimation in generalized linear models with random effects summary a conceptually very simple but general algorithm for the estimation of the fixed effects random effects and components of dispersion in generalized linear models with random effects is proposed conditions are described under which the algorithm yields approximate maximum likelihood or quasi maximum likelihood estimates of the fixed effects and dispersion components and approximate empirical bayes estimates of the random effects the algorithm is applied to two data sets to illustrate the estimation of components of dispersion and the modelling of overdispersion

integration theory on the zero sets of polyfold fredholm sections we construct an integration theory for sc differential forms on oriented branched ep subgroupoid for which stokes theorem holds true the construction is compatible with equivalences between ep groupoids and so gives rise to an integration theory for branched suborbifolds of polyfolds examples are the solutions sets of proper oriented fredholm sections of strong polyfold bundles for which we obtain invariants this way

a score test for testing a zero inflated poisson regression model against zero inflated negative binomial alternatives count data often show a higher incidence of zero counts than would be expected if the data were poisson distributed zero inflated poisson regression models are a useful class of models for such data but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the poisson distribution we therefore provide a score test for testing zero inflated poisson regression models against zero inflated negative binomial alternatives

some current cfd issues relevant to the incompressible navier stokes equations abstract the goals of this paper are to carefully define a particular class of well set incompressible navier stokes problems in the continuum partial differential equation pde setting and to discuss some relevant and sometimes poorly understood issues related to these well posed pde problems both in the continuum world and in its computer counterpart emphasized are three common formulations used to generate computer codes the primitive variable velocity pressure formulation and two derived variable formulations pressure poisson equation and vorticity transport equation

random effects models for serial observations with binary response this paper presents a general mixed model for the analysis of serial dichotomous responses provided by a panel of study participants each subject s serial responses are assumed to arise from a logistic model but with regression coefficients that vary between subjects the logistic regression parameters are assumed to be normally distributed in the population inference is based upon maximum likelihood estimation of fixed effects and variance components and empirical bayes estimation of random effects exact solutions are analytically and computationally infeasible but an approximation based on the mode of the posterior distribution of the random parameters is proposed and is implemented by means of the em algorithm this approximate method is compared with a simpler two step method proposed by korn and whittemore using data from a panel study of asthmatics originally described in that paper one advantage of the estimation strategy described here is the ability to use all of the data including that from subjects with insufficient data to permit fitting of a separate logistic regression model as required by the korn and whittemore method however the new method is computationally intensive

polyfolds cobordisms and the strong weinstein conjecture abstract we prove the strong weinstein conjecture for closed contact manifolds that appear as the concave boundary of a symplectic cobordism admitting an essential local foliation by holomorphic spheres

simulation of incompressible turbulent flows revue des simulations d ecoulements turbulents modeles de turbulence avec moyenne de reynolds traitement des ecoulements geometriquement complexes les lois de conservation et leur interaction avec les methodes numeriques methodes de discretisation techniques de resolution autres approches du calcul des ecoulements turbulents

a taylor galerkin method for convective transport problems a method is described to derive finite element schemes for the scalar convection equation in one or more space dimensions to produce accurate temporal differencing the method employs forward time taylor series expansions including time derivatives of second and third order which are evaluated from the governing partial differential equation this yields a generalized time discretized equation which is successively discretized in space by means of the standard bubnov galerkin finite element method the technique is illustrated first in one space dimension with linear elements and euler leap frog and crank nicolson time stepping several interesting relations with standard galerkin and recently developed petrov galerkin methods emerge and the new taylor galerkin schemes are found to exhibit particularly high phase accuracy with minimal numerical damping the method is successively extended to deal with variable coefficient problems and multi dimensional situations

a score test for overdispersion in zero inflated poisson mixed regression model count data with extra zeros are common in many medical applications the zero inflated poisson zip regression model is useful to analyse such data for hierarchical or correlated count data where the observations are either clustered or represent repeated outcomes from individual subjects a class of zip mixed regression models may be appropriate however the zip parameter estimates can be severely biased if the non zero counts are overdispersed in relation to the poisson distribution in this paper a score test is proposed for testing the zip mixed regression model against the zero inflated negative binomial alternative sampling distribution and power of the test statistic are evaluated by simulation studies the results show that the test statistic performs satisfactorily under a wide range of conditions the test procedure is applied to pancreas disorder length of stay that comprised mainly same day separations and simultaneous prolonged hospitalizations

sensitivity of score tests for zero inflation in count data in many biomedical applications count data have a large proportion of zeros and the zero inflated poisson regression zip model may be appropriate a popular score test for zero inflation comparing the zip model to a standard poisson regression model was given by van den broek similarly for count data that exhibit extra zeros and are simultaneously overdispersed a score test for testing the zip model against a zero inflated negative binomial alternative was proposed by ridout hinde and demetrio however these test statistics are sensitive to anomalous cases in the data and incorrect inferences concerning the choice of model may be drawn in this paper diagnostic measures are derived to assess the influence of observations on the score statistics two examples that motivated the application of zero inflated regression models are considered to illustrate the importance of sensitivity analysis of the zero inflation tests

approximate inference in generalized linear mixed models statistical approaches to overdispersion correlated errors shrinkage estimation and smoothing of regression relationships may be encompassed within the framework of the generalized linear mixed model glmm given an unobserved vector of random effects observations are assumed to be conditionally independent with means that depend on the linear predictor through a specified link function and conditional variances that are specified by a variance function known prior weights and a scale factor the random effects are assumed to be normally distributed with mean zero and dispersion matrix depending on unknown variance components for problems involving time series spatial aggregation and smoothing the dispersion may be specified in terms of a rank deficient inverse covariance matrix approximation of the marginal quasi likelihood using laplace s method leads eventually to estimating equations based on penalized quasilikelihood or pql for the mean parameters and pseudo likelihood for the variances im

zero inflated poisson and binomial regression with random effects a case study summary in a 1992 technometrics paper lambert 1992 34 1 14 described zero inflated poisson zip regression a class of models for count data with excess zeros in a zip model a count response variable is assumed to be distributed as a mixture of a poisson distribution and a distribution with point mass of one at zero with mixing probability p both p and are allowed to depend on covariates through canonical link generalized linear models in this paper we adapt lambert s methodology to an upper bounded count situation thereby obtaining a zero inflated binomial zip model in addition we add to the flexibility of these fixed effects models by incorporating random effects so that e g the within subject correlation and between subject heterogeneity typical of repeated measures data can be accommodated we motivate develop and illustrate the methods described here with an example from horticulture where both upper bounded count binomial type and unbounded count poisson type data with excess zeros were collected in a repeated measures designed experiment

finite element analysis of oscillatory flow with heat transfer inside a square cavity in this work a semi implicit projection type finite element method is applied to solve the incompressible oscillatory cavity flow with heat transfer the two dimensional time dependent navier stokes and energy equations are numerically integrated by a time split galerkin finite element method using direct matrix solvers the time accuracy of the method was tested by calculating the transient buoyancy driven flow in a square cavity with differentially heated vertical walls the oscillatory cavity flow is then studied considering the effects of heat transfer reynolds number and oscillatory stokes number to measure the stability of the scheme for such a high singularity phenomenon the proposed scheme is found to be stable and convergent for high rayleigh numbers and will be applicable to general problems involving flow and heat transfer especially in three dimensions

aerodynamic and aeroelastic analysis of bundled cables by numerical simulation abstract a numerical model for the aerodynamic and aeroelastic analysis of bundled cables commonly used in energy transmission lines is presented in this work the bundles were idealized by a sectional model representing the section at the mid span between two supporting towers a slightly compressible viscous fluid was considered and the two dimensional flow was analyzed using a two step explicit method with an arbitrary eulerian lagrangean description a taylor series expansion was used in time and the classical galerkin technique with the finite element method were used for space discretization turbulence was modeled using large eddy simulation with the classical smagorinsky s sub grid scale model the set of cables forms a single body with elastic constrains working mechanically coupled being each cable linked to the others by spacers the fluid structure interaction was taken into account considering equilibrium and compatibility conditions at the fluid solid interfaces and the resulting dynamical equilibrium equation was solved using the newmark s method

finite element solution of the unsteady navier stokes equations by a fractional step method abstract a finite element method is presented for the numerical simulation of time dependent incompressible viscous flows the method is based on a fractional step approach to the time integration of the navier stokes equations in which only the incompressibility condition is treated implicitly this leads to a computational scheme of extremely simple algorithmic structure that is particularly attractive for cost effective solutions of large scale problems numerical results indicate the versatility and effectiveness of the proposed method

the analysis of binomial data by a generalized linear mixed model summary methods for generalized linear models are extended to provide estimates of location and variance parameters for mixed models fitted to binomial data formed by classifying samples from an underlying normal distribution the method estimates the parameters directly on the underlying scale for a balanced one way random effects model the variance estimator simplifies to the usual analysis of variance one the estimation of variances and the prediction of random effects for binomial traits is required by animal breeders the predictors given are analogous to best linear unbiased predictors henderson 1973 but differ from those presented by harville mee 1984

involutions obstructions and mirror symmetry abstract consider a maslov zero lagrangian submanifold diffeomorphic to a lie group on which an anti symplectic involution acts by the inverse map of the group we show that the fukaya a endomorphism algebra of such a lagrangian is quasi isomorphic to its de rham cohomology tensored with the novikov field in particular it is unobstructed formal and its floer and de rham cohomologies coincide our result implies that the smooth fibers of a large class of singular lagrangian fibrations are unobstructed and their floer and de rham cohomologies coincide this is a step in the syz and family floer cohomology approaches to mirror symmetry more generally our result continues to hold if the lagrangian has cohomology the free graded algebra on a graded vector space v concentrated in odd degree and the anti symplectic involution acts on the cohomology of the lagrangian by the induced map of negative the identity on v it suffices for the maslov class to vanish modulo 4

local influence measure of zero inflated generalized poisson mixture regression models in many practical applications count data often exhibit greater or less variability than allowed by the equality of mean and variance referred to as overdispersion underdispersion and there are several reasons that may lead to the overdispersion underdispersion such as zero inflation and mixture moreover if the count data are distributed as a generalized poisson or a negative binomial distribution that accommodates extra variation not explained by a simple poisson or a binomial model then the dispersion occurs too in this paper we deal with a class of two component zero inflated generalized poisson mixture regression models to fit such data and propose a local influence measure procedure for model comparison and statistical diagnostics at first we formally develop a general model framework that unifies zero inflation mixture as well as overdispersion underdispersion simultaneously and then we mainly investigate two types of perturbation schemes the global and individual perturbation schemes for perturbing various model assumptions and detecting influential observations also we obtain the corresponding local influence measures our method is novel for count data analysis and can be used to explore these essential issues such as zero inflation mixture and dispersion related to zero inflated generalized poisson mixture models on the basis of the results of model comparison we could further conduct the sensitivity analysis of perturbation as well as hypothesis test with more accuracy finally we employ here a simulation study and a real example to illustrate the proposed local influence measures copyright 2012 john wiley sons ltd

a hierarchical finite mixture model that accommodates zero inflated counts non independence and heterogeneity a number of mixture modeling approaches assume both normality and independent observations however these two assumptions are at odds with the reality of many data sets which are often characterized by an abundance of zero valued or highly skewed observations as well as observations from biologically related i e non independent subjects we present here a finite mixture model with a zero inflated poisson regression component that may be applied to both types of data this flexible approach allows the use of covariates to model both the poisson mean and rate of zero inflation and can incorporate random effects to accommodate non independent observations we demonstrate the utility of this approach by applying these models to a candidate endophenotype for schizophrenia but the same methods are applicable to other types of data characterized by zero inflation and non independence

semi implicit taylor galerkin finite element methods for incompressible viscous flows abstract semi implicit taylor galerkin finite element methods are developed for solution of incompressible flows with heat transfer in the methods the primitive variables are split into two parts and the equations for the one part are solved using a semi implicit taylor galerkin method while the equations for the second part are dealt with by an implicit method the methods are tested and analysed by numerical calculations of several problems

contact homology and virtual fundamental cycles we give a construction of contact homology in the sense of eliashberg givental hofer specifically we construct coherent virtual fundamental cycles on the relevant compactified moduli spaces of pseudo holomorphic curves the aim of this work is to provide a rigorous construction of contact homology an invariant of contact manifolds and exact symplectic cobordisms due to eliashberg givental hofer eli98 egh00 the contact homology of y is defined in terms of pseudo holomorphic curve counts in the sense of gromov gro85 in the symplectization r y unfortunately the moduli spaces of such curves often suffer from a severe lack of transversality and for this reason it has until now remained an important open problem to define the relevant curve counts in full generality we will use the framework developed in par15 to construct coherent virtual fundamental cycles on the moduli spaces in question thus giving rise to the desired curve counts our methods are quite general and should apply equally well to many other moduli spaces of interest previously a number of important special cases of contact homology and closely related invariants have been constructed rigorously using generic and or automatic transversality techniques cylindrical contact homology of some three manifolds was constructed by bao

models for longitudinal data a generalized estimating equation approach this article discusses extensions of generalized linear models for the analysis of longitudinal data two approaches are considered subject specific ss models in which heterogeneity in regression parameters is explicitly modelled and population averaged pa models in which the aggregate response for the population is the focus we use a generalized estimating equation approach to fit both classes of models for discrete and continuous outcomes when the subject specific parameters are assumed to follow a gaussian distribution simple relationships between the pa and ss parameters are available the methods are illustrated with an analysis of data on mother s smoking and children s respiratory disease

a time marching boundary element method for two dimensional incompressible thermally coupled flows abstract a time marching boundary element method is developed for the solution of two dimensional incompressible thermally coupled flows by applying the operator splitting technique and time difference discretization semi discretized semi implicit differential equations are obtained and then green s function method is used to derive time marching integral equations and time marching boundary integral equations the relation between the time marching boundary integral equation and an explicit time integration scheme is brought to light the boundary element and finite element approaches are employed to solve the resulting time marching boundary integral equations numerical calculations have been carried out for the free convection flow in a unit square cavity for testing the accuracy and efficiency of the present method

time accurate computation of unsteady free surface flows using an ale segregated equal order fem abstract arbitrary lagrangian eulerian ale finite element formulations based on segregated equal order interpolation are presented with the aim of computing unsteady free surface flows time accurately a standing vortex problem is solved using both fixed and moving grids to design a solution method which is time accurate in the sense that it conserves vortex kinetic energy it turns out that the chorin type simple algorithm serves this purpose satisfactorily when it is used in conjunction with the galerkin spatial discretization and the crank nicolson temporal discretization then a small amplitude sloshing problem is solved to assure that the crank nicolson central difference scheme among others used for discretizing the kinematic condition preserves the oscillating amplitude of the free surface lastly the most time accurate numerical technique thus designed is applied to solve a solitary wave propagation problem which shows that the predicted maximum run up heights for various initial heights are in good agreement with existing experiment

a score test for zero inflation in correlated count data to account for the preponderance of zero counts and simultaneous correlation of observations a class of zero inflated poisson mixed regression models is applicable for accommodating the within cluster dependence in this paper a score test for zero inflation is developed for assessing correlated count data with excess zeros the sampling distribution and the power of the test statistic are evaluated by simulation studies the results show that the test statistic performs satisfactorily under a wide range of conditions the test procedure is further illustrated using a data set on recurrent urinary tract infections