on the asymptotic bias of the ordinary least squares estimator of the tobit model this paper presents a precise characterization of the bias of least squares in two limited dependent variable models the tobit model and the truncated regression model for the cases considered the method of moments can be used to correct the bias of ols for more general cases the results provide approximations which appear to be relatively robust 13 and o in this paper we present a precise characterization of that bias for the particular case in which xt as well as is normally distributed we also show that the bias of the ols slope estimator can be corrected by dividing each estimate by the sample proportion of nonlimit observations other structural parameters can be consistently estimated in a similar fashion we present some evidence on the effect of nonnormality with respect to the predictions obtained in the normal model the case in which the sample contains only nonlimit observation the truncated regression model is considered elsewhere olsen 7 we analyze the relationship between his results and ours and derive some predictions of the normal model with respect to the seriousness of truncation bias

computer intensive methods in statistical regression this is a survey of modern developments in statistical regression written for the mathematically educated nonstatistician it begins with a review of the traditional theory of least squares curve fitting modern developments in regression theory have developed in response to the practical limitations of the least squares approach recent progress has been made feasible by the electronic computer which frees statisticians from the confines of mathematical tractability topics discussed include robust regression bootstrap measures of variability local smoothing and cross validation projection pursuit mallows c p criterion stein estimation generalized regression for poisson data and regression methods for censored data all of the methods are illustrated with real life examples

estimation of limited dependent variable models by ordinary least squares and the method of moments abstract under certain conditions a broad class of qualitative and limited dependent variable models can be consistently estimated by the method of moments using a non iterative correction to the ordinary least squares estimator with only a small loss of efficiency compared to maximum likelihood estimation the class of models is that obtained from a classical multinormal regression by any type of censoring or truncation and includes the tobit probit two limit probit truncated regression and some variants of the sample selection models the paper derives the estimators and their asymptotic covariance matrices

sylow numbers and nilpotent hall subgroups let be a set of primes and g a finite group we characterize the existence of a nilpotent hall subgroup of g in terms of the number of sylow subgroups for the primes in

abelian sylow subgroups in a finite group ii abstract let p 3 5 be a prime we prove that sylow p subgroups of a finite group g are abelian if and only if the class sizes of the p elements of g are all coprime to p this gives a solution to a problem posed by r brauer in 1956 for p 3 5

distribution free and link free estimation for the sample selection model abstract the prevalent estimation methods for the sample selection model rely heavily on parametric assumptions and are sensitive to departures from the underlying parametric assumptions see e g goldberger 1983 we propose an alternative estimation method the corrected maximum likelihood estimate which is consistent for the slope vector in the outcome equation up to a multiplicative scalar even through the parametric model on which the estimate is based might be misspecified as an important corollary it follows from our result that olsen s 1980 corrected ordinary least squares estimate is consistent if the outcome equation is linear without requiring olsen s assumptions on the joint error distribution

equivariant splendid rickard equivalences abstract broue s conjecture says that if a finite group h has an abelian sylow p subgroup p then the principal blocks of h and n h p are splendidly rickard equivalent in this paper broue s conjecture is reduced to simple groups with a stability condition a structure theorem on finite groups with abelian sylow p subgroups due to kimmerle and sandling is used

the adjoint projection pursuit regression abstract consider a projection pursuit regression model y g x e with an arbitrary monotonic link function g we assume the link function is unknown thus we can only estimate the direction of that is the ratios among the components of say 1 2 the direction of is a useful estimand that measures say how many units of x 2 is equivalent to one unit of x 1 in terms of potency in affecting the outcome y projection pursuit regression usually solves the equation cov x y e y x 0 as an alternative we propose to solve the adjoint equation cov x e x x y 0 the adjoint equation has the advantage that e x x might be easier to estimate than e y x we establish two main results for the population case first is the unique solution up to a multiplicative scalar to the adjoint equation second satisfies a fixed point property based on a modified least squares regression derived from the adjoint equation we apply the population results to two important

composition factors from the table of marks let b g be the burnside ring for a finite group g and let t g be the table of marks of g it is known that in general neither b g nor t g determines the finite group g that is one can easily construct pairs of non isomorphic finite groups such that their table of marks is the same hence their burnside rings are isomorphic in this note we show that the composition factors of g are determined by the table of marks t g

character tables and defect groups abstract let b be a block of a finite group g with defect group d we prove that the exponent of the center of d is determined by the character table of g in particular we show that d is cyclic if and only if b contains a large family of irreducible p conjugate characters more generally for abelian d we obtain an explicit formula for the exponent of d in terms of character values in small cases even the isomorphism type of d is determined in this situation moreover it can read off from the character table whether d d 4 where d denotes the commutator subgroup of d we also propose a new characterization of nilpotent blocks in terms of the character table

nilpotent and abelian hall subgroups in finite groups the research of the first second fourth fifth and sixth authors was supported by the prometeo generalitat valenciana proyectos mtm2010 15296 mtm2010 19938 c03 02 fundacio bancaixa p11b2010 47 and fondos feder the third author gratefully acknowledges financial support by erc advanced grant 291512 the seventh author was supported by the nsa grant h98230 13 1 0229 the eighth author gratefully acknowledges the support of the nsf grants dms 0901241 and dms 1201374

non parametric analysis of a generalized regression model the maximum rank correlation estimator the paper considers estimation of a model yi d f x i 0 ui where the composite transformation d f is only specified that d r r is non degenerate monotonic and f r2 r is strictly monotonic in each of its variables the paper thus generalizes standard data analysis which assumes that the functional form of d f is known and additive the estimator which it proposes is the maximum rank correlation estimator which is non parametric in the functional form of d f and non parametric in the distribution of the error terms ui the estimator is shown to be strongly consistent for the parameters 0 up to a scale coefficient

slicing regression a link free regression method slicing regression a link free regression m e t h o d author s naihua duan and k e r c h a u l i s o u r c e the annals of statistics v o l 19 n o 2 t u n 1991 p p 5 0 5 5 3 0 p u b l i s h e d b y institute of mathematical statistics s t a b l e u r l http www jstor org stable 2242072 accessed 16 05 2011 your use of the jstor archive indicates your acceptance of jstor s terms and conditions of use available at http www jstor org page info about policies terms jsp jstor s terms and conditions of use provides in part that unless you have obtained prior permission you may not download an entire issue of a journal or multiple copies of articles and you may use content in the jstor archive only for your personal non commercial use please contact the publisher regarding any further use of this work publisher contact information may be obtained at http www jstor org action showpublisher publishercode ims each copy of any part of a jstor transmission must contain the same copyright notice that appears on the screen or printed page of such transmission jstor is a not for profit service that helps scholars researchers and students discover use and build upon a wide range of content in a trusted digital archive we use information technology and tools to increase productivity and facilitate new forms of scholarship for more information about jstor please contact support jstor org http www jstor org

characters of relative p degree over normal subgroups let z be a normal subgroup of a finite group g let irr z be an irreducible complex character of z and let p be a prime number if p does not divide the integers 1 1 for all irr g lying over then we prove that the sylow p subgroups of g z are abelian this theorem which generalizes the gluck wolf theorem to arbitrary finite groups is one of the principal obstacles to proving the celebrated brauer height zero conjecture

optimized schwarz waveform relaxation for the primitive equations of the ocean in this article we are interested in the derivation of efficient domain decomposition methods for the viscous primitive equations of the ocean we consider the rotating three dimensional incompressible hydrostatic navier stokes equations with free surface performing an asymptotic analysis of the system in the regime of small rossby numbers we compute an approximate dirichlet to neumann operator and build an optimized schwarz waveform relaxation algorithm we establish that the algorithm is well defined and provide numerical evidence of the convergence of the method