a characterization of bloch type spaces on the unit ball of cn abstract in this paper we generalize holland walsh s characterization of the bloch space and stroethoff s characterization of the little bloch space on the unit disk to bloch spaces and little bloch spaces on the unit ball of c n for 0 2

characterization of fuzzy preference structures through łukasiewicz triplets in this paper we characterize the reconstruction of a fuzzy set from its subsets by means of lukasiewicz triplets this result allows us to introduce a new definition of fuzzy strict preference which is also satisfied in the crisp framework the usual definitions of fuzzy indifference and fuzzy incomparability together with this one enable to construct and to characterize fuzzy preference structures from a reflexive fuzzy binary relation

higher order properties of gmm and generalized empirical likelihood estimators in an effort to improve the small sample properties of generalized method of moments gmm estimators a number of alternative estimators have been suggested these include empirical likelihood el continuous updating and exponential tilting estimators we show that these estimators share a common structure being members of a class of generalized empirical likelihood gel estimators we use this structure to compare their higher order asymptotic properties we find that gel has no asymptotic bias due to correlation of the moment functions with their jacobian eliminating an important source of bias for gmm in models with endogeneity we also find that el has no asymptotic bias from estimating the optimal weight matrix eliminating a further important source of bias for gmm in panel data models we give bias corrected gmm and gel estimators we also show that bias corrected el inherits the higher order property of maximum likelihood that it is higher order asymptotically efficient relative to the other bias corrected estimators

finite sample properties of maximum likelihood estimator in spatial models we investigate the finite sample properties of the maximum likelihood estimator for the spatial autoregressive model a stochastic expansion of the score function is used to develop the second order bias and mean squared error of the maximum likelihood estimator we show that the results can be expressed in terms of the expectations of cross products of quadratic forms or ratios of quadratic forms in a normal vector which can be evaluated using the top order invariant polynomial our numerical calculations demonstrate that the second order behaviors of the maximum likelihood estimator depend on the degree of sparseness of the weights matrix

an axiomatic approach to fuzzy preference modelling abstract we propose an axiomatic approach to the definition of fuzzy strict preference p indifference i and incomparability j associated with a fuzzy preference relation r expression for p i and j are given via solving two systems of functional equations

on the formulation of wald tests of nonlinear restrictions this paper utilizes asymptotic expansions of the edgeworth type to investigate alternative forms of the wald test of nonlinear restrictions some formulae for the asymptotic expansion of the distribution of the wald statistic are provided for a general case that should include most econometric applications when specialized to the simple cases that have been studied recently in the literature these formulae are found to explain rather well the discrepancies in sampling behavior that have been observed by other authors it is further shown how the corrections delivered by edgeworth expansions may be used to find transformations of the restrictions which accelerate convergence to the asymptotic distribution

a valued ferrers relation for interval comparison the paper deals with the valued comparison of intervals for decision making interval orders are classical preference structures where the comparison of intervals is done in an ordinal way in this paper we focus on valued comparison where more information especially the distance between end points of intervals is used in order to have more sophisticated preference structures the generalization of an interval order as a valued structure requires the choice of de morgan triplets we propose a valued outranking relation for interval comparison and show that it satisfies different definitions of valued interval orders using different de morgan triplet the decomposition of our outranking relation into preference and indifference provides a valued preference structure where the preference is t transitive and monotone

transitivity bounds in additive fuzzy preference structures transitivity plays a crucial role in preference modeling and related fields in this paper we discuss this property in the general context of additive fuzzy preference structures of particular interest is the decomposition of a large preference relation r in its symmetric part i indifference relation and its asymmetric part p strict preference relation by means of a so called indifference generator i given the type of transitivity of a large preference relation r w r t a conjunctor and a generator we establish basic lower bounds and general upper bounds on the transitivity of p and i these bounds are due to the careful design of generic counterexamples moreover we identify the situations in which these bounds are effectively reached thereby establishing connections with interesting properties such as dominance bisymmetry the 1 lipschitz property and rotation invariance

holomorphic functions and quasiconformal mappings with smooth moduli abstract we discuss the implication f g f g where f is a holomorphic function resp a quasiconformal mapping on a domain g c n resp g r n and g is the lipschitz space associated with a majorant

valued preference structures abstract an approach to the axiomatics of valued preference modelling is suggested in the framework of this approach general definitions of strict preference indifference and incomparability relations associated with a valued preference relation are established via solving a system of functional equations any solution of this system satisfies most of the classical properties characterizations of important particular solutions are also proved

construction of global fuzzy preference structures from two parameter single criterion fuzzy outranking relations in this paper we deal with the construction of global fuzzy preference structures from two parameter single criterion fuzzy outranking relations proposed in 10 and which are based on the aggregation of outranking indices associated with a cuts we consider two ways of constructing global fuzzy preference structures i aggregate the two parameter single criterion fuzzy outranking relations and then construct the global fuzzy preference structures and ii construct global fuzzy preference structures and then aggregate the single criterion fuzzy preference indifference and incomparability relations we also investigate the case where these two ways of proceeding lead to the same results

estimates on bloch constants for planar harmonic mappings the schwarz lemma and bloch constants for planar bounded harmonic mappings are considered sharper form and better estimates are obtained our results improve the one made by dorff and nowak as well as by chen gauthier and hengartner

fuzzy sets and decision analysis abstract this survey points out recent advances in multiple attribute decision making methods dealing with fuzzy or ill defined information fuzzy maut as well as fuzzy outranking methods are reviewed aggregation procedures choice problems and treatment of interactive attributes are covered trends in research and open problems are indicated

on certain quasiconformal and elliptic mappings abstract let d be the closure of the unit disk d in the complex plane c and g be a continuous function in d in this paper we discuss some characterizations of elliptic mappings f satisfying the poisson s equation f g in d and then establish some sharp distortion theorems on elliptic mappings with the finite perimeter and the finite radial length respectively the obtained results are the extension of the corresponding classical results

fuzzy interval and semi orders abstract the seminal paper by luce econometrica 24 1956 178 on intransitive indifference provoked a rich body of research on how to model such a type of indifference interval orders and semi orders play a central role in the modelization of intransitive indifference this paper is an attempt to fuzzify interval orders and semi orders we use an additive fuzzy preference structure to argue for a fuzzification of interval and semi orders we show that fuzzy interval orders are to a degree semi orders however against expectations we cannot show that fuzzy interval graphs are to a degree fuzzy indifference graphs

on characterizations of bloch type hardy type and lipschitz type spaces in this paper we establish a bloch type growth theorem for generalized bloch type spaces and discuss relationships between dirichlet type spaces and hardy type spaces on certain classes of complex valued functions then we present some applications to non homogeneous yukawa pdes we also consider some properties of the lipschitz type spaces on certain classes of complex valued functions finally we will study a class of composition operators on these spaces

traces of fuzzy binary relations abstract in this paper the right and left trace of a fuzzy binary relation is defined and investigated basic properties of a fuzzy relation such as reflexivity different kinds of transitivity linearity etc are characterized by means of its traces

the second order bias and mean squared error of nonlinear estimators abstract despite the now widespread use of nonlinear estimators their finite sample properties have received very little attention in either the statistics or econometrics literature we partially redress this problem by deriving and examining the second order bias and mean squared error of a fairly wide class of nonlinear estimators which includes nonlinear least squares maximum likelihood and many generalized method of moments estimators as special cases a number of examples are provided the results from a monte carlo exercise demonstrate how the results can be applied for improved inferences

the second order bias and mean squared error of estimators in time series models we develop analytical results on the second order bias and mean squared error of estimators in time series models these results provide a unified approach to developing the properties of a large class of estimators in linear and nonlinear time series models and they are valid for both normal and nonnormal samples of observations and where the regressors are stochastic the estimators included are the generalized method of moments maximum likelihood least squares and other extremum estimators our general results are applied to four time series models we investigate the effects of nonnormality on the second order bias results for two of these models while for all four models the second order bias and mean squared error results are given under normality numerical results for some of these models are also presented

properties of the cue estimator and a modification with moments abstract in this paper we analyze properties of the continuous updating estimator cue proposed by hansen et al 1996 which has been suggested as a solution to the finite sample bias problems of the two step gmm estimator we show that the estimator should be expected to perform poorly in finite samples under weak identification in particular the estimator is not guaranteed to have finite moments of any order we propose the regularized cue rcue as a solution to this problem the rcue solves a modification of the first order conditions for the cue estimator and is shown to be asymptotically equivalent to cue under many weak moment asymptotics our theoretical findings are confirmed by extensive monte carlo studies

bias reduction in nonlinear and dynamic panels in the presence of cross section dependence abstract fixed effects estimation of nonlinear dynamic panel models is subject to the incidental parameter issue leading to a biased asymptotic distribution while this problem has been studied extensively in the literature a general analysis allowing for both serial and cross sectional dependence is missing in this paper we investigate the large n t theory of the profile and integrated likelihood estimators allowing for dependence across both dimensions we show that under stronger dependence types the asymptotic bias disappears but a o p 1 t small sample bias remains we provide bias correction and inference methods and also obtain primitive conditions for asymptotic normality under various dependence settings

managing non homogeneous information in group decision making within the frame of decision aid literature decision making problems with multiple sources of information have drawn the attention of researchers from a wide spectrum of disciplines in decision situations with multiple individuals each one has his own knowledge on the alternatives of the decision problem the use of information assessed in different domains is not a seldom situation this non homogeneous information can be represented as values belonging to domains with different nature as linguistic numerical and interval valued or can be values assessed in label sets with different granularity multi granular linguistic information decision processes for solving these problems are composed by two phases aggregation and exploitation the main problem to deal with non homogeneous contexts is how to aggregate the information assessed in these contexts in this paper taking as base the 2 tuple fuzzy linguistic representation model we shall develop an aggregation process for dealing with non homogeneous contexts in first place we shall develop an aggregation process for combining numerical interval valued and linguistic information afterwards we shall propose different extensions of this process to deal with contexts in which can appear other type of information as intuitionistic fuzzy sets or multi granular linguistic information

a general method for third order bias and variance corrections on a nonlinear estimator motivated by a recent study of bao and ullah 2007a on finite sample properties of mle in the pure sar spatial autoregressive model a general method for third order bias and variance corrections on a nonlinear estimator is proposed based on stochastic expansion and bootstrap working with concentrated estimating equation simplifies greatly the high order expansions for bias and variance a simple bootstrap procedure overcomes a major difficulty in analytically evaluating expectations of various quantities in the expansions the method is then studied in detail using a more general sar model with its effectiveness in correcting bias and improving inference fully demonstrated by extensive monte carlo experiments compared with the analytical approach the proposed approach is much simpler and has a much wider applicability the validity of the bootstrap procedure is formally established the proposed method is then extended to the case of more than one nonlinear estimator

smoothed quantile regression for panel data abstract this paper studies fixed effects estimation of quantile regression models for panel data under an asymptotic framework where both the numbers of individuals and time periods grow at the same rate we show that the fixed effects estimator for the smoothed objective function has a limiting normal distribution with a bias in the mean and provide the analytic form of the asymptotic bias we propose a one step bias correction estimator based on the analytic bias formula obtained from the asymptotic analysis importantly our results cover the case that observations are dependent over time we illustrate the effects of the bias correction through simulations

long difference instrumental variables estimation for dynamic panel models with fixed effects this paper proposes a new instrumental variables estimator for a dynamic panel model with fixed effects with good bias and mean squared error properties even when identification of the model becomes weak near the unit circle we adopt a weak instrument asymptotic approximation to study the behavior of various estimators near the unit circle we show that an estimator based on long differencing the model is much less biased than conventional implementations of the gmm estimator for the dynamic panel model we also show that under the weak instrument approximation conventional gmm estimators are dominated in terms of mean squared error by an estimator with far less moment conditions the long difference ld estimator mimics the infeasible optimal procedure through its reliance on a small set of moment conditions

specification tests based on mcmc output abstract two test statistics are proposed to determine model specification after a model is estimated by an mcmc method the first test is the mcmc version of ios a test and its asymptotic null distribution is normal the second test is motivated from the power enhancement technique of fan et al 2015 it combines a component j 1 that tests a null point hypothesis in an expanded model and a power enhancement component j 0 obtained from the first test it is shown that j 0 converges to zero when the null model is correctly specified and diverges when the null model is misspecified also shown is that j 1 is asymptotically 2 distributed suggesting that the second test is asymptotically pivotal when the null model is correctly specified the main feature of the first test is that no alternative model is needed the second test has several properties first its size distortion is small and hence bootstrap methods can be avoided second it is easy to compute from mcmc output and hence is applicable to a wide range of models including latent variable models for which frequentist methods are difficult to use third when the test statistic rejects the null model and j 1 takes a large value the test suggests the source of misspecification the finite sample performance is investigated using simulated data the method is illustrated in a linear regression model a linear state space model and a stochastic volatility model using real data

weak and strong fuzzy interval orders abstract the purpose of this paper is to introduce and investigate the fuzzification of the classical interval order one of the most interesting classical preference structures without incomparability in this study we consider fuzzy preference structures as defined by de baets et al fuzzy preference structures without incomparability receive special attention their fuzzy preference and fuzzy large preference relations share certain types of the t n ferrers property two special types of the j n ferrers property are introduced the weak ferrers and strong ferrers properties the classical interval order is briefly reviewed t fuzzy interval orders are introduced and it is shown that their fuzzy preference relation is sup t transitive two special types of t fuzzy interval orders are considered weak and strong fuzzy interval orders corresponding to transforms of w and to m the particular intermediate role of the weak ferrers property of the fuzzy preference relation of a fps without incomparability is demonstrated on the one hand it is a necessary condition for the fps to be a strong fuzzy interval order while on the other hand it is a sufficient condition for this structure to be a weak fuzzy interval order finally the concept of an cut of a fps is introduced leading to an interesting characterization of the strong ferrers property of a fps without incomparability

construction of a two parameters fuzzy outranking relation from fuzzy evaluations at the early stages of design process several design concepts are proposed as potential solutions the selection of the most appropriate one is based on their evaluation with respect to several conflicting criteria in this paper we consider the case where the evaluations of design concepts with respect to different criteria are represented by means of fuzzy numbers we deal with the construction of a two parameters fuzzy outranking relation from fuzzy evaluations it is based on the aggregation of outranking indices associated with alpha cuts this fuzzy outranking index allows the decision maker to adopt different strategies by choosing a degree of optimism and a degree of aggressiveness

asymptotic expansions of the information matrix test statistic the information matrix im test is shown to have a finite sample distribution which is poorly approximated by its asymptotic x 2 distribution in models and sample sizes commonly encountered in applied econometric research the quality of the x2 approximation depends upon the method chosen to compute the test failure to exploit restrictions on the covariance matrix of the test can lead to a test with appalling finite sample properties order o n 1 approximations to the exact distribution of an efficient form of the im test are reported these are developed from asymptotic expansions of the edgeworth and cornish fisher types they are compared with monte carlo estimates of the finite sample distribution of the test and are found to be superior to the usual x2 approximations in sample sizes of the magnitude found in applied micro econometric work the methods developed in the paper are applied to normal and exponential models and to normal regression models results are provided for the full im test and for heteroskedasticity and nonnormality diagnostic tests which are special cases of the im test in geieral the quality of alternative approximations is sensitive to covariate design however commonly used nonnormality tests are found to have distributions which to order o n 1 are invariant under changes in covariate design this leads to simple design and parameter invariant size corrections for nonnormality tests

indicators of fuzzy relations in this paper first we give the definitions of various indicators of fuzzy relations and their basic properties then we investigate the relationships between these indicators particularly between those of t transitivity negative s transitivity t s semitransitivity and t s ferrers property the investigation is divided into three parts results in the general case results under a condition proposed by peng et al and results under special t norms and t conorms on account of our research certain results on fuzzy relations in the literature are extended to the degree description

modeling rationality in a linguistic framework in classical decision theory there exists a large class of rationality models which try to capture different kinds of behavior when individuals compare by pairs a set of alternatives all these models assume that decision makers have dichotomous preferences however in real decisions individuals feel different degrees of preference in this paper we have checked the mentioned models in a real case where different kinds of linguistic preferences are allowed after the empirical analysis the main conclusion is that the fulfillment of rational conditions decreases when individuals have non extreme preferences based on the obtained empirical evidences we propose some classes of transitivity conditions in the framework of linguistic preferences

strict preference relations based on weak t norms abstract in this paper we introduce and investigate weak t norms and related concepts in order to give a general representation of valued strict preference relations associated with a given valued preference relation all the well known forms of valued strict preference relations are particular cases of our results moreover when some types of rationality assumptions are made our unified approach seems to be the only possible one

jackknife and analytical bias reduction for nonlinear panel models fixed effects estimators of panel models can be severely biased because of the well known incidental parameters problem we show that this bias can be reduced by using a panel jackknife or an analytical bias correction motivated by large t we give bias corrections for averages over the fixed effects as well as model parameters we find large bias reductions from using these approaches in examples we consider asymptotics where t grows with n as an approximation to the properties of the estimators in econometric applications we show that if t grows at the same rate as n the fixed effects estimator is asymptotically biased so that asymptotic confidence intervals are incorrect but that they are correct for the panel jackknife we show t growing faster than n 1 3 suffices for correctness of the analytic correction a property we also conjecture for the jackknife

on a family of connectives for fuzzy sets abstract in this paper we find the general solution of the functional equation s t x y t x n y x where s is a t conorm t is a t norm and n is a strong negation on the unit interval in particular the result yields a family of connectives for fuzzy sets

generalized bloch spaces integral means of hyperbolic harmonic mappings in the unit ball abstract in this paper we investigate the properties of hyperbolic harmonic mappings in the unit ball b n in r n n 2 firstly we establish necessary and sufficient conditions for a hyperbolic harmonic mapping to be in the bloch space b b n and the generalized bloch space l b a 0 b n respectively secondly we discuss the relationship between the integral means of hyperbolic harmonic mappings and that of their gradients the obtained results are the generalizations of hardy and littlewood s related ones in the setting of hyperbolic harmonic mappings finally we characterize the weak uniform boundedness property of hyperbolic harmonic mappings in terms of the quasihyperbolic metric

the use of fuzzy outranking relations in preference modelling this paper deals with preference modelling in the context of decision aid in this framework conflicting systems of logic uncertain knowledge ambiguous positions are always present in order to tackle this problem a multiple criteria methodology is proposed mainly based on fuzzy outranking relations introduced both at one dimensional and multi dimensional levels some properties of outranking relations are investigated such relations are then combined using fuzzy logical connectives to generate relational systems of fuzzy preferences that are shown to be very useful to reflect the vagueness of information in the various preference situations that may be considered in the modelling process

edgeworth approximations for semiparametric instrumental variable estimators and test statistics abstract we establish the validity of higher order asymptotic expansions to the distribution of a version of the nonlinear semiparametric instrumental variable estimator considered in newey econometrica 58 1990 809 as well as to the distribution of a wald statistic derived from it we employ local polynomial smoothing with variable bandwidth which includes local linear kernel and a version of nearest neighbor estimates as special cases our expansions are valid to order n 2e for some 0

conditional extensions of fuzzy preorders abstract the problem of embedding incomplete into complete relations has been an important topic of research in the context of crisp relations and their applications several variations of the acclaimed szpilrajn s theorem have been provided inclusive of the case when some order conditions between elements are imposed on the extension we extend the analysis of that topic by alcantud to the fuzzy case by appealing to generators to decompose fuzzy preference relations into strict preference and indifference relations we give general extension results for the corresponding concept of compatible extension of a fuzzy reflexive relation then we investigate the conditions under which compatible order extensions exist such that certain elements are connected by the asymmetric part resp and certain other elements by the symmetric part to respective elements with degree 1

integrating multiplicative preference relations in a multipurpose decision making model based on fuzzy preference relations the aim of this paper is to study the integration of multiplicative preference relation as a preference representation structure in fuzzy multipurpose decision makingproblems assumingfuzzy multipurpose decision makingproblems under di4erent preference representation structures ordering utilities and fuzzy preference relations and using the fuzzy preference relations as uniform representation elements the multiplicative preference relations are incorporated in the decision problem by means of a transformation function between multiplicative and fuzzy preference relations a consistency study of this transformation function which demonstrates that it does not change the informative content of multiplicative preference relation is shown as a consequence a selection process based on fuzzy majority for multipurpose decision makingproblems under multiplicative preference relations is presented to design it an aggregation operator of information called ordered weighted geometric operator is introduced and two choice degrees the quanti7er guided dominance degree and the quanti7er guided non dominance degree are de7ned for multiplicative preference relations c 2001 elsevier science b v all rights reserved

additive decomposition of fuzzy pre orders fuzzy pre orders reflexive and min transitive fuzzy relations constitute an important class of fuzzy relations by means of an indifference generator a fuzzy pre order can be decomposed additively into two parts an indifference relation and a strict preference relation when using a frank t norm as indifference generator we fully characterize the transitivity of these parts only in case the minimum operator is used as generator both parts are min transitive the transitivity of the indifference relation is determined by the frank t norms while the transitivity of the strict preference relation is determined by transforms of the nilpotent minimum t norm

fuzzy relational compositions abstract this paper investigates the fuzzy relational compositions defined by bandler and kohout it is indicated that these compositions have to be modified in order to capture the desired interpretation several alternative definitions are suggested and discussed the paper concludes with an overview of the properties of these improved fuzzy relational compositions

fuzzy preference structures without incomparability abstract in this paper we establish important relationships between the basic properties of the components of a fuzzy preference structure without incomparability this study is carried out for the fuzzy preference structures introduced recently by de baets van de walle and kerre a set of remarkable theorems gives detailed insight in the relationships between the sup t transitivity of the fuzzy preference and indifference relations and the sup t transitivity of the fuzzy large preference relation several paths of thought involving t norms with or without zero divisors are explored and where required illustrative counterexamples confirm the falsity of certain implications finally we introduce the t n ferrers property of a binary fuzzy relation and show that the fuzzy preference and fuzzy large preference relations share certain types of this ferrers property

the stochastic difference between econometric statistics dans un contexte general et dans divers cas particuliers on calcule l ordre en probabilite de la difference entre des racines consistantes d equations d estimation rivales

on fuzzy strict preference indifference and incomparability relations abstract the existence of fuzzy models for strict preference indifference and incomparability satisfying all classical properties is established a particular class of such models is completely described

local intrinsic dimension estimation by generalized linear modeling we propose a method for intrinsic dimension estimation by fitting the power of distance from an inspection point and the number of samples included inside a ball with a radius equal to the distance to a regression model we estimate the goodness of fit then by using the maximum likelihood method we estimate the local intrinsic dimension around the inspection point the proposed method is shown to be comparable to conventional methods in global intrinsic dimension estimation experiments furthermore we experimentally show that the proposed method outperforms a conventional local dimension estimation method

gel estimation and tests of spatial autoregressive models abstract this paper considers the generalized empirical likelihood gel estimation and tests of high order spatial autoregressive sar models by exploring an inherent martingale structure the gel estimator has the same asymptotic distribution as the generalized method of moments estimator explored with same moment conditions for estimation but circumvents a first step estimation of the optimal weighting matrix with a preliminary estimator and thus can be robust to unknown heteroskedasticity and non normality while the gel removes the asymptotic bias from the preliminary estimator and partially removes the bias due to the correlation between the moment conditions and their jacobian the empirical likelihood as a special member of gels further partially removes the bias from estimating the second moment matrix we also formulate the gel overidentification test moran s i test and gel ratio tests for parameter restrictions and non nested hypotheses while some of the conventional tests might not be robust to non normality and or unknown heteroskedasticity the corresponding gel tests can be robust

a plea for the use of lukasiewicz triplets in the definition of fuzzy preference structures i general argumentation abstract the generalization of the concept of a classical or crisp preference structure to that of a fuzzy preference structure expressing degrees of strict preference indifference and incomparability among a set of alternatives requires the choice of a de morgan triplet i e of a triangular norm and an involutive negator the resulting concept is only meaningful provided that this choice allows the representation of truly fuzzy preferences more specifically one of the degrees of strict preference indifference or incomparability should always be unconstrained to the preference modeller this intuitive requirement is violated when choosing a triangular norm without zero divisors since in that case fuzzy preference structures reduce to classical preference structures and hence none of the degrees can be freely assigned furthermore it is shown that the choice of a continuous non archimedean triangular norm having zero divisors is not compatible with our basic requirement the sets of degrees of strict preference indifference and incomparability in 0 1 are always bounded from above by a value strictly smaller than 1 these fundamental results imply that when working with a continuous triangular norm only archimedean ones having zero divisors are suitable candidates these arguments sufficiently support our plea for the use of ukasiewicz triplets in the definition of fuzzy preference structures

fuzzy semi orders the case of t norms without zero divisors for crisp relations the concept of a semi order can be stated in a number of equivalent ways when trying to extend this concept to the fuzzy setting we observe that the generalized definitions fail to be equivalent in this contribution we discuss which is the most natural definition of a fuzzy semi order and study the hierarchy among the alternative definitions in particular when using a t norm without zero divisors

reverse estimates in growth spaces let h b d denote the space of holomorphic functions on the unit ball b d of mathbb c d given a radial doubling weight w we construct functions f g in h b 1 such that f g is comparable to w also we obtain similar results for b d d 2 and for circular strictly convex domains with smooth boundary as an application we study weighted composition operators and related integral operators on growth spaces of holomorphic functions

transitivity frameworks for reciprocal relations cycle transitivity versus fg transitivity for a reciprocal relation q on a set of alternatives a two transitivity frameworks which generalize both t transitivity and stochastic transitivity are compared the framework of cycle transitivity introduced by the present authors soc choice welf to appear and which is based upon the ordering of the numbers q a b q b c and q c a for all a b c a 3 and the framework of fg transitivity introduced by switalski fuzzy sets and systems 137 2003 85 as an immediate generalization of stochastic transitivity the rules that enable to express fg transitivity in the form of cycle transitivity and cycle transitivity in the form of fg transitivity illustrate that for reciprocal relations the concept of cycle transitivity provides a framework that can cover more types of transitivity than does the concept of fg transitivity

on transitivity of strict preference relations abstract a general notion of a strict preference relation associated with a preference relation valued in a semilattice with difference is introduced if a preference relation is valued in a linear scale then the associated strict preference relation is always transitive in contrast for some nonlinear scales transitivity of a preference relation does not imply transitivity of the associated strict preference relation the identity x y z x z y z is characteristic for the class of lower semilattices with difference for which associated strict preference relations preserve transitivity of preference relations

characterizations of α bloch spaces on the unit ball abstract we obtain a characterization of the bloch space for any 0 in the unit ball of c n in terms of f z f w z w moreover a new characterization for the bloch space is given

a general model for deriving preference structures from data in this paper we comment upon the integrated model for valued preferences introduced by fodor ovchinnikov and roubens in particular while on one hand we revise basic assumptions and point out their intuitive meaning on the other hand we propose an alternative mathematical justification of such a model which allows not only a better understanding of the obtained results but also a functional characterization of the whole family of solutions

an alternative definition for fuzzy interval orders the class of interval orders is one of the most studied classes of preference structures without incomparability in the theory of classical preference modelling in this paper we propose a generalization of the classical definition of interval order and strict interval order we focus our attention on two important classes of interval orders and strict interval orders which are respectively defined by means of a strong de morgan triplet and a min max de morgan triplet

interval valued preference structures different languages that are offered to model vague preferences are reviewed and an interval valued language is proposed to resolve a particular difficulty encountered with other languages it is shown that interval valued languages are well defined for de morgan triples constructed by continuous triangular norms conorms and a strong negation function a new transitivity condition for vague preferences is suggested and its relationships to known transitivity conditions are established a complete characterization of intervalvalued preference structures is also provided

gmm gel serial correlation and asymptotic bias for stationary time series models with serial correlation we consider generalized method of moments gmm estimators that use heteroskedasticity and autocorrelation consistent hac positive definite weight matrices and generalized empirical likelihood gel estimators based on smoothed moment conditions following the analysis of newey and smith 2004 for independent observations we derive second order asymptotic biases of these estimators the inspection of bias expressions reveals that the use of smoothed gel in contrast to gmm removes the bias component associated with the correlation between the moment function and its derivative while the bias component associated with third moments depends on the employed kernel function we also analyze the case of no serial correlation and find that the seemingly unnecessary smoothing and hac estimation can reduce the bias for some of the estimators

bias in the estimation of the mean reversion parameter in continuous time models abstract it is well known that for continuous time models with a linear drift standard estimation methods yield biased estimators for the mean reversion parameter both in finite discrete samples and in large in fill samples in this paper we obtain two expressions to approximate the bias of the least squares maximum likelihood estimator of the mean reversion parameter in the ornstein uhlenbeck process with a known long run mean when discretely sampled data are available the first expression mimics the bias formula of marriott and pope 1954 for the discrete time model simulations show that this expression does not work satisfactorily when the speed of mean reversion is slow slow mean reversion corresponds to the near unit root situation and is empirically realistic for financial time series an improvement is made in the second expression where a nonlinear correction term is included into the bias formula it is shown that the nonlinear term is important in the near unit root situation simulations indicate that the second expression captures the magnitude the curvature and the non monotonicity of the actual bias better than the first expression

fixed effects estimation of structural parameters and marginal effects in panel probit models fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem in this paper i characterize the leading term of a large t expansion of the bias of the mle and estimators of average marginal effects in parametric fixed effects panel binary choice models for probit index coefficients the former term is proportional to the true value of the coefficients being estimated this result allows me to derive a lower bound for the bias of the mle i then show that the resulting fixed effects estimates of ratios of coefficients and average marginal effects exhibit no bias in the absence of heterogeneity and negligible bias for a wide variety of distributions of regressors and individual effects in the presence of heterogeneity i subsequently propose new bias corrected estimators of index coefficients and marginal effects with improved finite sample properties for linear and nonlinear models with predetermined regressors

collective transitivity in majorities based on difference in support a common criticism to simple majority voting rule is the slight support that such rule demands to declare an alternative as a winner among the distinct majority rules used for diminishing this handicap we focus on majorities based on difference in support with these majorities voters are allowed to show intensities of preference among alternatives through reciprocal preference relations these majorities also take into account the difference in support between alternatives in order to select the winner in this paper we have provided some necessary and sufficient conditions for ensuring transitive collective decisions generated by majorities based on difference in support for all the profiles of individual reciprocal preference relations these conditions involve both the thresholds of support and some individual rationality assumptions that are related to transitivity in the framework of reciprocal preference relations

on the fuzzification of the classical definition of preference structure this paper is divided into two main parts in the first part we propose an appropriate definition for fuzzy preference structures the definition is based on two main features the first feature consists in using a strong de morgan triplet as a model for the classical de morgan triplet the second feature consists in choosing a particular completeness condition such that when it is combined with some other conditions all the generalized completeness conditions are satisfied these two features of our definition are justified by a set of remarkable theorems and propositions proving some equivalencies we can write this definition with only three minimal and independent conditions in the second part we use the new definition to analyse two methods of construction of fuzzy strict preference indifference and incomparability relations from a given reflexive fuzzy relation on the one hand we prove that the triplets of fuzzy strict preference indifference and incomparability relations constructed from a reflexive fuzzy relation by using a same t norm are not necessarily fuzzy preference structures on the other hand we prove that those generated by the method of fodor and roubens are fuzzy preference structures according to the proposed definition