cuntz krieger algebras of infinite graphs and matrices we show that the cuntz krieger algebras of infinite graphs and infinite 0 1 matrices can be approximated by those of finite graphs we then use these approximations to deduce the main uniqueness theorems for cuntz krieger algebras and to compute their k theory since the finite approximating graphs have sinks we have to calculate the k theory of cuntz krieger algebras of graphs with sinks and the direct methods we use to do this should be of independent interest

dynamical systems associated to separated graphs graph algebras and paradoxical decompositions abstract we attach to each finite bipartite separated graph e c a partial dynamical system e c f where e c is a zero dimensional metrizable compact space f is a finitely generated free group and is a continuous partial action of f on e c the full crossed product c algebra o e c c e c f is shown to be a canonical quotient of the graph c algebra c e c of the separated graph e c similarly we prove that for any field k the algebraic crossed product l k ab e c c k e c alg f is a canonical quotient of the leavitt path algebra l k e c of e c the monoid v l k ab e c of isomorphism classes of finitely generated projective modules over l k ab e c is explicitly computed in terms of monoids associated to a canonical sequence of separated graphs using this we are able to construct an action of a finitely generated free group f on a zero dimensional metrizable compact space z such that the type semigroup s z f k is not almost unperforated where k denotes the algebra of clopen subsets of z finally we obtain a characterization of the separated graphs e c such that the canonical partial action of f on e c is topologically free

the limits of the solutions of a nonautonomous linear delay difference equation abstract consider the system of linear delay difference equations where the coefficients a j n are square matrices and k j and l j are nonnegative integers in this note we show that if the coefficients are small then every solution of the above equation tends to a constant vector as n and the value of the limit can be characterized by a special solution of the matrix equation and the initial conditions

sequentially additive nonignorable missing data modelling using auxiliary marginal information summarywe study a class of missingness mechanisms referred to as sequentially additive nonignorable for modelling multivariate data with item nonresponse these mechanisms explicitly allow the probability of nonresponse for each variable to depend on the value of that variable thereby representing nonignorable missingness mechanisms these missing data models are identified by making use of auxiliary information on marginal distributions such as marginal probabilities for multivariate categorical variables or moments for numeric variables we prove identification results and illustrate the use of these mechanisms in an application

graphs groupoids and cuntz krieger algebras we associate to each locally finite directed graphgtwo locally compact groupoidsgandg the unit space ofgis the space of one sided infinite paths ing andg is the reduction ofgto the space of paths emanating from a distinguished vertex we show that under certain conditions theirc algebras are morita equivalent the groupoidc algebrac g is the cuntz krieger algebra of an infinite 0 1 matrix defined byg and that the algebrasc g contain thec algebras used by doplicher and roberts in their duality theory for compact groups we then analyse the ideal structure of these groupoidc algebras using the general theory of renault and calculate theirk theory

slope estimation in the presence of informative right censoring modeling the number of observations as a geometric random variable summary a method is proposed for the estimation of rate of change from incomplete longitudinal data where the number of observations made for each subject is assumed to vary depending on the level of the response variable the proposed method involves a random slope model in which the number of observations is modeled as a geometric distribution with its mean dependent on the individual subject s rate of change the method adjusts for informative right censoring and provides estimates of the slopes of individual subjects as well as of the population under noninformative right censoring these estimators of the slopes are equivalent to bayes estimators fearn 1975 biometrika 62 89 100 the simulation study demonstrates that in cases where the censoring process is informative the proposed estimator is more efficient than either the unweighted or weighted estimator of slope the method is illustrated by the analysis of renal transplant data

amenability and paradoxicality in semigroups and c algebras abstract we analyze the dichotomy amenable paradoxical in the context of discrete countable unital semigroups and corresponding semigroup rings we consider also folner type characterizations of amenability and give an example of a semigroup whose semigroup ring is algebraically amenable but has no folner sequence in the context of inverse semigroups s we give a characterization of invariant measures on s in the sense of day in terms of two notions domain measurability and localization given a unital representation of s in terms of partial bijections on some set x we define a natural generalization of the uniform roe algebra of a group which we denote by r x we show that the following notions are then equivalent 1 x is domain measurable 2 x is not paradoxical 3 x satisfies the domain folner condition 4 there is an algebraically amenable dense subalgebra of r x 5 r x has an amenable trace 6 r x is not properly infinite and 7 0 1 in the k 0 group of r x we also show that any tracial state on r x is amenable moreover taking into account the localization condition we give several c algebraic characterizations of the amenability of x finally we show that for a certain class of inverse semigroups the quasidiagonality of c r x implies the amenability of x the reverse implication which is a natural generalization of rosenberg s conjecture to this context is false

the c algebras of finitely aligned higher rank graphs we generalise the theory of cuntz krieger families and graph algebras to the class of finitely aligned k graphs this class contains in particular all row finite k graphs the cuntz krieger relations for non row finite k graphs look significantly different from the usual ones and this substantially complicates the analysis of the graph algebra we prove a gauge invariant uniqueness theorem and a cuntz krieger uniqueness theorem for the c algebras of finitely aligned k graphs

semiparametric pseudo likelihoods in generalized linear models with nonignorable missing data we consider identifiability and estimation in a generalized linear model in which the response variable and some covariates have missing values and the missing data mechanism is nonignorable and unspecified we adopt a pseudo likelihood approach that makes use of an instrumental variable to help identifying unknown parameters in the presence of nonignorable missing data explicit conditions for the identifiability of parameters are given some asymptotic properties of the parameter estimators based on maximizing the pseudo likelihood are established explicit asymptotic covariance matrix and its estimator are also derived in some cases for the numerical maximization of the pseudo likelihood we develop a two step iteration algorithm that decomposes a nonconcave maximization problem into two problems of maximizing concave functions some simulation results and an application to a dataset from cotton factory workers are also presented

multiple imputation in mixture models for nonignorable nonresponse with follow ups abstract one approach to inference for means or linear regression parameters when the outcome is subject to nonignorable nonresponse is mixture modeling mixture models assume separate parameters for respondents and nonrespondents implementation by multiple imputation consists of repeatedly filling in missing values for nonrespondents estimating parameters using the filled in data and then adjusting for variability between imputations we evaluated the performance of this scheme using simulated data with a 25 sample of nonrespondents followed up we conclude that it provides a generally satisfactory and robust approach to inference for means and regression parameters in this case although a greater number of imputations may be required for good performance compared to the number required for estimation when nonresponse is ignorable

the leavitt path algebra of a graph abstract for any row finite graph e and any field k we construct the leavitt path algebra l e having coefficients in k when k is the field of complex numbers then l e is the algebraic analog of the cuntz krieger algebra c e described in i raeburn graph algebras in cbms reg conf ser math vol 103 amer math soc 2005 the matrix rings m n k and the leavitt algebras l 1 n appear as algebras of the form l e for various graphs e in our main result we give necessary and sufficient conditions on e which imply that l e is simple

sharp conditions for existence of nontrivial invariant cones of nonnegative initial values of difference equations it is proved that an arbitrary scalar difference equation has a nontrivial invariant cone in the set of the nonnegative initial values if and only if the associated characteristic equation has a positive root by using this fact there is given a construction of the maximal invariant cone in the set of nonnegative initial values via a positive root of the associated characteristic equation finally the present results are compared with some earlier ones which were obtained for delay differential equations in the same direction

c algebras generated by elements of a unitary matrix abstract let unnc be the unital c algebra generated by the elements uij 1 i j n satisfying the relations which make uij a unitary matrix unnc is isomorphic to the relative commutant of mn in the amalgamated product m n c c t define un rednc to be the relative commutant of mn in the reduced amalgamated product of m n c c t with respect to the usual traces we show that unnc has no nontrivial projections and that un rednc is a simple c algebra with no nontrivial projections we also compute the k groups of unnc as well as those of the noncommutative grassmanian gnnc

the behavior of solutions of linear volterra difference equations with infinite delay a class of linear volterra difference equations with infinite delay is considered a basic theorem on the behavior of solutions is established and as a corollary a useful exponential estimate for solutions is obtained and a stability criterion is derived these results are achieved via an appropriate positive root of the corresponding characteristic equation

general methods for analysing repeated measures we present an overview of issues and methods for analysing repeated measures of a continuous random variable we discuss modelling the mean vector and covariance structure statistical efficiency regression diagnostics and discrepancies between longitudinal and cross sectional methods we illustrate key points with examples and discuss areas requiring further development

periodic first order linear neutral delay differential equations some new asymptotic and stability results are given for a first order linear neutral delay differential equation with periodic coefficients and constant delays the asymptotic behavior of the solutions and the stability of the trivial solution are described by the use of an appropriate real root of an equation which is in a sense the corresponding characteristic equation

on the behavior of the solutions to periodic linear delay differential and difference equations some new results on the behavior of the solutions to periodic linear delay differential equations as well as to periodic linear delay difference equations are given these results are obtained by the use of two distinct roots of the corresponding so called characteristic equation

the behavior of solutions of linear integro differential equations with unbounded delay abstract a basic theorem on the behavior of solutions of scalar linear integro differential equations with unbounded delay is established as a consequence of this theorem a stability criterion is obtained

regression analysis for categorical variables with outcome subject to nonignorable nonresponse abstract we develop a log linear model for categorical response subject to nonignorable nonresponse the paper differs from fay 1986 in its focus on estimation and hypothesis testing in a regression setting as opposed to imputation in a multivariate setting we present several new results concerning the existence of solutions on the boundary of the parameter space and the construction of confidence intervals for estimates we illustrate the method by estimating the proportion of voters preferring truman in a 1948 preelection poll mosteller hyman mccarthy marks and truman 1949 results may depend strongly on the model assumed for nonresponse goodness of fit tests are available for comparing alternative models

a semiparametric estimation of mean functionals with nonignorable missing data parameter estimation with nonignorable missing data is a challenging problem in statistics the fully parametric approach for joint modeling of the response model and the population model can produce results that are quite sensitive to the failure of the assumed model we propose a more robust modeling approach by considering the model for the nonresponding part as an exponential tilting of the model for the responding part the exponential tilting model can be justified under the assumption that the response probability can be expressed as a semiparametric logistic regression model in this paper based on the exponential tilting model we propose a semiparametric estimation method of mean functionals with nonignorable missing data a semiparametric logistic regression model is assumed for the response probability and a nonparametric regression approach for missing data discussed in cheng 1994 is used in the estimator by adopting nonparametric components for the model the estimation method can be mad

amenability for fell bundles given a fell bundle b over a discrete group we construct its reduced cross sectional algebra c r b in analogy with the reduced crossed products defined for c dynamical systems when the reduced and full cross sectional algebras of b are isomorphic we say that the bundle is amenable we then formulate an approximation property which we prove to be a sufficient condition for amenability a theory of graded c algebras possessing a conditional expectation is developed with an eye on the fell bundle that one naturally associates to the grading we show for instance that all such algebras are isomorphic to c r b when the bundle is amenable we also study induced ideals in graded c algebras and obtain a generalization of results of str til and voiculescu on af algebras and of nica on quasi lattice ordered groups a brief comment is made on the relevance to our theory of a certain open problem in the theory of exact c algebras an application is given to the case of an fn grading of the cuntz krieger algebras oa recently discovered by quigg and raeburn specifically we show that the cuntz krieger bundle satisfies the approximation property and hence is amenable for all matrices a with entries in 0 1 even if a does not satisfy the well known property i studied by cuntz and krieger in their paper

branching systems and representations of cohn leavitt path algebras of separated graphs abstract for each separated graph e c we construct a family of branching systems over a set x and show how each branching system induces a representation of the cohn leavitt path algebra associated with e c as homomorphisms over the module of functions in x we also prove that the abelianized cohn leavitt path algebra of a separated graph with no loops can be written as an amalgamated free product of abelianized cohn leavitt algebras that can be faithfully represented via branching systems

missing covariates in generalized linear models when the missing data mechanism is non ignorable we propose a method for estimating parameters in generalized linear models with missing covariates and a non ignorable missing data mechanism we use a multinomial model for the missing data indicators and propose a joint distribution for them which can be written as a sequence of one dimensional conditional distributions with each one dimensional conditional distribution consisting of a logistic regression we allow the covariates to be either categorical or continuous the joint covariate distribution is also modelled via a sequence of one dimensional conditional distributions and the response variable is assumed to be completely observed we derive the e and m steps of the em algorithm with non ignorable missing covariate data for categorical covariates we derive a closed form expression for the e and m steps of the em algorithm for obtaining the maximum likelihood estimates mles for continuous covariates we use a monte carlo version of the em algorithm to obtain the mles via the gibbs sampler computational techniques for gibbs sampling are proposed and implemented the parametric form of the assumed missing data mechanism itself is not testable from the data and thus the non ignorable modelling considered here can be viewed as a sensitivity analysis concerning a more complicated model therefore although a model may have passed the tests for a certain missing data mechanism this does not mean that we have captured even approximately the correct missing data mechanism hence model checking for the missing data mechanism and sensitivity analyses play an important role in this problem and are discussed in detail several simulations are given to demonstrate the methodology in addition a real data set from a melanoma cancer clinical trial is presented to illustrate the methods proposed

purely infinite simple reduced c algebras of one relator separated graphs abstract given a separated graph e c there are two different c algebras associated to it the full graph c algebra c e c and the reduced one c red e c for a large class of separated graphs e c we prove that c red e c either is purely infinite simple or admits a faithful tracial state the main tool we use to show pure infiniteness of reduced graph c algebras is a generalization to the amalgamated case of a result on purely infinite simple free products due to dykema

the behavior of the solutions of periodic linear neutral delay difference equations some new asymptotic nonoscillation and stability criteria for linear neutral delay difference equations with periodic coefficients and constant delays are given the results are obtained via a positive root with suitable properties of an associated equation which is in a sense the corresponding characteristic equation

analysis of crossover designs with multivariate response crossover designs involve observing the same response variate under different experimental conditions for each subject univariate methods are commonly used for analysis of data arising in these designs but multivariate procedures offer a more general approach the general multivariate linear model provides a natural framework for the simplest data structure as well as more complex settings with two or more response variates and measurements repeated over time multivariate models for crossover designs provide a unified approach that clarifies specification of hypotheses assumptions required and testing procedures in a wide class of applications that include longitudinal data as a special case we focus on the 2 2 crossover design but also describe models for analysing more complex crossover designs

convex subshifts separated bratteli diagrams and ideal structure of tame separated graph algebras abstract we introduce a new class of partial actions of free groups on totally disconnected compact hausdorff spaces which we call convex subshifts these serve as an abstract framework for the partial actions associated with finite separated graphs in much the same way as classical subshifts generalize the edge shift of a finite graph we define the notion of a finite type convex subshift and show that any such subshift is kakutani equivalent to the partial action associated with a finite bipartite separated graph we then study the ideal structure of both the full and the reduced tame graph c algebras o e c and o r e c of a separated graph e c and of the abelianized leavitt path algebra l k ab e c as well these algebras are the reduced crossed products with respect to the above mentioned partial actions and we prove that there is a lattice isomorphism between the lattice of induced ideals and the lattice of hereditary d saturated subsets of a certain infinite separated graph f d built from e c called the separated bratteli diagram of e c we finally use these tools to study simplicity and primeness of the tame separated graph algebras

protective estimation of mixed effects logistic regression when data are not missing at random we consider estimation of mixed effects logistic regression models for longitudinal data when missing outcomes are not missing at random a typology of missingness mechanisms is presented that includes missingness dependent on observed or missing current outcomes observed or missing lagged outcomes and subject specific effects when data are not missing at random consistent estimation by maximum marginal likelihood generally requires correct parametric modelling of the missingness mechanism which hinges on unverifiable assumptions we show that standard maximum conditional likelihood estimators are protective in the sense that they are consistent for monotone or intermittent missing data under a wide range of missingness mechanisms our approach requires neither specification of parametric models for the missingness mechanism nor refreshment samples and is straightforward to implement in standard software 2013 biometrika trust

representing finitely generated refinement monoids as graph monoids abstract graph monoids arise naturally in the study of non stable k theory of graph c algebras and leavitt path algebras they play also an important role in the current approaches to the realization problem for von neumann regular rings in this paper we characterize when a finitely generated conical refinement monoid can be represented as a graph monoid the characterization is expressed in terms of the behavior of the structural maps of the associated i system at the free primes of the monoid

models for nonresponse in sample surveys abstract the literature on the analysis of incomplete data using models is reviewed in the context of nonresponse in sample surveys the modeling approach provides a large body of methods for handling unit and item nonresponse some of which cannot be derived from the randomization theory of inference for surveys key concepts from the literature on incomplete data such as factorizations of the likelihood for special data patterns the em algorithm for general data patterns and ignorability of the response mechanism are discussed within the survey context model based procedures are related to common methods for handling nonresponse in surveys such as weighting or imputation of means within subclasses of the population

a noninformative bayesian approach to interval estimation in finite population sampling abstract a noninformative bayesian approach to interval estimation in finite population sampling is discussed given the sample this method introduces the polya distribution as a pseudo posterior distribution over the unobserved members of the population in many cases this distribution yields interval estimates similar to those of standard frequentist theory in addition it can be used in situations where the standard methods are difficult to apply for example in producing an interval estimate for the ratio of two medians we also consider related point estimation problems and observe that estimators derived from the pseudo posterior often perform better than classical alternatives

random truncation and neutrinos we study in this article the energies of neutrinos observed in the irvine michigan brookhaven detector near fairport ohio the chance of observing a neutrino with a given amount of energy is a function of the sensitivity or trigger efficiency of the detector because some of the neutrinos were undetected the distribution of the observed data is randomly truncated we consider maximum likelihood estimation of the parameters for the randomly truncated normal distribution as well as a normal model for power transformations to obtain confidence regions for the parameters both asymptotic normal theory and approximate likelihood based confidence regions are constructed monte carlo investigations are used to study the properties of maximum likelihood estimators for randomly truncated normal distributions the simulation study shows that confidence regions based on the asymptotic normal theory perform very poorly whereas the approximate likelihood based regions provide coverages closer to the nominal level

non ignorable missing covariates in generalized linear models we propose a likelihood method for estimating parameters in generalized linear models with missing covariates and a non ignorable missing data mechanism in this paper we focus on one missing covariate we use a logistic model for the probability that the covariate is missing and allow this probability to depend on the incomplete covariate we allow the covariates including the incomplete covariate to be either categorical or continuous we propose an em algorithm in this case for a missing categorical covariate we derive a closed form expression for the e and m steps of the em algorithm for obtaining the maximum likelihood estimates mles for a missing continuous covariate we use a monte carlo version of the em algorithm to obtain the mles via the gibbs sampler the methodology is illustrated using an example from a breast cancer clinical trial in which time to disease progression is the outcome and the incomplete covariate is a quality of life physical well being score taken after the start of therapy this score may be missing because the patients are sicker so this covariate could be non ignorably missing

k theory for partial crossed products by discrete groups the notion of a partial crossed product of a c algebra by the group of integers introduced by r exel is generalized to a partial crossed product by any discrete group a reduced partial crossed product is defined and some of the standard facts relating amenability and k amenability to ordinary crossed products are extended to this case the exact sequence of pimsner and voiculescu for reduced crossed products by the free group on n generators is generalized to this setting this result is used to calculate the k groups of an amalgamated product of two finite dimensional c algebras over a common maximal commutative subalgebra

pattern mixture models for multivariate incomplete data consider a random sample on variables x1 xv with some values of xv missing selection models specify the distribution of x1 xv over respondents and nonrespondents to xv and the conditional distribution that xv is missing given x1 xv in contrast pattern mixture models specify the conditional distribution of x 1 xv given that xv is observed or missing respectively and the marginal distribution of the binary indicator for whether or not xv is missing for multivariate data with a general pattern of missing values the literature has tended to adopt the selection modeling approach see for example little and rubin here pattern mixture models are proposed for this more general problem pattern mixture models are chronically underidentified in particular for the case of univariate nonresponse mentioned above there are no data on the distribution of xv given x1 xv 1 in the stratum with xv missing thus the models require restrictions or prior information to identify the paramet

associativity of crossed products by partial actions enveloping actions and partial representations given a partial action a of a group g on an associative algebra a we consider the crossed product a g using the algebras of multipliers we generalize a result of exel 1997 on the associativity of a g obtained in the context of c algebras in particular we prove that a g is associative provided that a is semiprime we also give a criterion for the existence of a global extension of a given partial action on an algebra and use crossed products to study relations between partial actions of groups on algebras and partial representations as an application we endow partial group algebras with a crossed product structure

the behavior of solutions of second order delay differential equations in this paper we study the behavior of solutions of second order delay differential equation y t p1y t p2y t q1y t q2y t where p1 p2 q1 q2 are real numbers is positive real number a basic theorem on the behavior of solutions is established as a consequence of this theorem a stability criterion is obtained

k theory for the tame c algebra of a separated graph abstract a separated graph is a pair e c consisting of a directed graph e and a set c v e 0 c v where each c v is a partition of the set of edges whose terminal vertex is v given a separated graph e c such that all the sets x c are finite the k theory of the graph c algebra c e c is known to be determined by the kernel and the cokernel of a certain map denoted by 1 c a e c from z c to z e 0 in this paper we compute the k theory of the tame graph c algebra o e c associated to e c which has been recently introduced by the authors letting denote the natural surjective homomorphism from c e c onto o e c we show that k 1 is a group isomorphism and that k 0 is a split monomorphism whose cokernel is a torsion free abelian group we also prove that this cokernel is a free abelian group when the graph e is finite and determine its generators in terms of a sequence of separated graphs e n c n n 1 naturally attached to e c on the way to showing our main results we obtain an explicit description of a connecting map arising in a six term exact sequence computing the k theory of an amalgamated free product and we also exhibit an explicit isomorphism between ker 1 c a e c and k 1 c e c

asymptotic behavior of a nonhomogeneous linear recurrence system consider the nonhomogeneous linear recurrence systemxn 1 a bn xn gn where a and bn n 0 1 are square matrices and gn n 0 1 are column vectors in this paper we describe in terms of the initial condition the asymptotic behavior of the solutions of this equation in the case when a has a simple dominant eigenvalue 0 n 0 bn and n 0 0 n gn the proof is based on the duality between the solutions of the above equation and the solutions of the associated adjoint equation as a consequence we obtain a similar result for higher order scalar equations

a class of pattern mixture models for normal incomplete data summary likelihood based methods are developed for analyzing a random sample on two continuous variables when values of one of the variables are missing normal maximum likelihood estimates when values are missing completely at random were derived by anderson 1957 they are also maximum likelihood providing the missing data mechanism is ignorable in rubin s 1976 sense that the mechanism depends only on observed data a new class of pattern mixture models little 1993 is described for the situation where missingness is assumed to depend on an arbitrary unspecified function of a linear combination of the two variables maximum likelihood for models in this class is straightforward and yields the estimates of anderson 1957 when missingness depends solely on the completely observed variable and the estimates of brown 1990 when missingness depends solely on the incompletely observed variable another choice of linear combination yields estimates from complete case analysis large sample and bayesian methods are described for this model the data do not supply information about the ratio of the coefficients of the linear combination that controls missingness if this ratio is not welldetermined based on prior knowledge a prior distribution can be specified and bayesian inference is then readily accomplished alternatively sensitivity of inferences can be displayed for a variety of choices of the ratio

alternative methods for cps income imputation abstract the u s bureau of the census imputes missing income items in the income supplement of the current population survey cps by a technique commonly known as the cps hot deck this article compares cps hot deck imputations of wages and salary amounts with alternatives based on regression models for the logarithm of wages and salary and for the wage rate comparisons are effected by comparing imputations with an internal revenue service irs wages and salary amount found by an exact match of cps data to irs records although limitations in the matching and in the comparison variable preclude a definitive conclusion we find that a the cps hot deck does not underestimate income aggregates to any serious extent b model based alternatives have slightly smaller mean absolute error than the hot deck when comparable data bases of respondents are used to carry out imputations and c multivariate models for imputing recipiency weeks and hours worked and earnings need to be developed to provide re

inference from coarse data via multiple imputation with application to age heaping abstract multiple imputation is applied to a demographic data set with coarse age measurements for tanzanian children the heaped ages are multiply imputed with plausible true ages using a a simple naive model and b a new relatively complex model that relates true age to the observed values of heaped age sex and anthropometric variables the imputed true ages are used to create valid inferences under the models and compare inferences across models thereby revealing sensitivity of inferences to prior specifications from naive to complex in addition diagnostic analyses applied to the imputed data are used to suggest which models appear most appropriate because it is not clear just what set of heaping intervals should be used the models are applied under various assumptions about the heaping rounding to the nearest year or half year versus a combination of rounding and truncation as practiced in the united states and medium versus wide heaping interval sizes the most striking conclusions ar

enveloping actions and takai duality for partial actions we show that any partial action on a topological space x is the restriction of a suitable global action called enveloping action that is essentially unique in the case of c algebras we prove that any partial action has a unique enveloping action up to morita equivalence and that the corresponding reduced crossed products are morita equivalent the study of the enveloping action up to morita equivalence reveals the form that takai duality takes for partial actions by applying our constructions we prove that the reduced crossed product of the reduced cross sectional algebra of a fell bundle by the dual coaction is liminal postliminal or nuclear if and only if so is the unit fiber of the bundle we also give a non commutative generalization of the well known fact that the integral curves of a vector field on a compact manifold are defined on all of r

identifiability of normal and normal mixture models with nonignorable missing data abstractmissing data problems arise in many applied research studies they may jeopardize statistical inference of the model of interest if the missing mechanism is nonignorable that is the missing mechanism depends on the missing values themselves even conditional on the observed data with a nonignorable missing mechanism the model of interest is often not identifiable without imposing further assumptions we find that even if the missing mechanism has a known parametric form the model is not identifiable without specifying a parametric outcome distribution although it is fundamental for valid statistical inference identifiability under nonignorable missing mechanisms is not established for many commonly used models in this article we first demonstrate identifiability of the normal distribution under monotone missing mechanisms we then extend it to the normal mixture and t mixture models with nonmonotone missing mechanisms we discover that models under the logistic missing mechanism are less

imputation of missing values when the probability of response depends on the variable being imputed abstract a method is developed for imputing missing values when the probability of response depends upon the variable being imputed the missing data problem is viewed as one of parameter estimation in a regression model with stochastic censoring of the dependent variable the prediction approach to imputation is used to solve this estimation problem wages and salaries are imputed to non respondents in the current population survey and the results are compared to the nonrespondents irs wage and salary data the stochastic censoring approach gives improved results relative to a prediction approach that ignores the response mechanism

parameter estimation from incomplete data in binomial regression when the missing data mechanism is nonignorable we propose a method for estimating parameters in binomial regression models when the response variable is missing and the missing data mechanism is nonignorable we assume throughout that the covariates are fully observed using a logit model for the missing data mechanism we show how parameter estimation can be accomplished using the em algorithm by the method of weights proposed in ibrahim 1990 journal of the american statistical association 85 765 769 an example from the six cities study ware et al 1984 american review of respiratory diseases 129 366 374 is presented to illustrate the method

asymptotic properties of solutions to linear non autonomous neutral differential equations abstract in this article we study asymptotic properties of solutions to first order linear neutral differential equations with variable coefficients and constant delays results are stated in terms of the solution to a characteristic equation by doing this we extend some of the results obtained for delay equations in j g dix ch g philos i k purnaras an asymptotic property of solutions to linear non autonomous delay differential equations electron j differential equations 2005 2005 1 9 to neutral equations

adjoining a universal inner inverse to a ring element abstract let r be an associative unital algebra over a field k let p be an element of r and let r r q p q p p we obtain normal forms for elements of r and for elements of r modules arising by extension of scalars from r modules the details depend on where in the chain p r r p p r r p p r r p r the unit 1 of r first appears this investigation is motivated by a hoped for application to the study of the possible forms of the monoid of isomorphism classes of finitely generated projective modules over a von neumann regular ring but that goal remains distant we end with a normal form result for the algebra obtained by tying together a k algebra r given with a nonzero element p satisfying 1 p r r p and a k algebra s given with a nonzero q satisfying 1 q s s q via the pair of relations p p q p q q p q

asymptotic behaviour of the solutions of a nonautonomous linear delay difference system abstract it is proved under appropriate assumptions that the solutions of a linear system of nonautonomous delay difference equations have finite limit at infinity the results are based on a transformation of the delay difference system into a first step recursion where the companion matrices are well treatable from our point of view our theory is illustrated by examples including a class of linear delay difference equations with unbounded coefficients

a bayesian procedure for imputing missing values in sample surveys abstract a new method is proposed for imputation of missing values in sample survey data the procedure uses standard statistical methodology permits a general specification of the nonresponse process and does not impose specific model assumptions prior information from past similar surveys or from other sources may be incorporated in a routine manner

c algebras of separated graphs the construction of the c algebra associated to a directed graph e is extended to incorporate a family c consisting of partitions of the sets of edges emanating from the vertices of e these c algebras c e c are analyzed in terms of their ideal theory and k theory mainly in the case of partitions by finite sets the groups k0 c e c and k1 c e c are completely described via a map built from an adjacency matrix associated to e c one application determines the k theory of the c algebras um nnc confirming a conjecture of mcclanahan a reduced c algebra cred e c is also introduced and studied a key tool in its construction is the existence of canonical faithful conditional expectations from the c algebra of any row finite graph to the c subalgebra generated by its vertices differences between cred e c and c e c such as simplicity versus non simplicity are exhibited in various examples related to some algebras studied by mcclanahan