the laurent series approach to structural modeling abstract caves and christensen 1980 have provided a procedure for displaying the regular regions of a flexible functional form in the 2 good homothetic and nonhomothetic cases and in the 3 good homothetic case we extend the procedure to the nonhomothetic 3 good case and we apply the extended procedure to the translog generalized leontief and minflex laurent flexible functional forms in addition we acquire the regular regions for the minflex laurent model in the 2 good nonhomothetic case and superimpose the resulting regions on those already found by caves and christensen for the translog and generalized leontief models we find that the new minflex laurent model generally has the largest regular regions of the three flexible functional forms in addition the regular region of the minflex laurent model is found to expand as real income increases as a result that model is particularly well suited for use with time series data which typically is characterized by positive long term growth trends in real income in such applications all recent data and future forecasts can be expected to lie within the regular region of the minflex laurent model although it is possible for some of the earliest data to fall outside that regular region the model s regular region nevertheless is sufficiently large to hold even all of those earliest data points in many data sets the regular region of each of the three models moves when the model s parameters are changed with the generalized leontief or translog model the regular region s shape location and size are unpredictable without prior knowledge of the model s parameters with either of those models the intersection of the model s regular regions as the parameters are changed is contained within a very small neighborhood of the one point at which we require the model to be regular with the minflex laurent model the primary properties of the regular regions are invariant to the values of the parameters and the intersection of the displayed regular regions is a very large unbounded set the width of that intersection increases without limit as real income increases

seminonparametric bayesian estimation of the asymptotically ideal production model abstract recently it has been shown that seminonparametric methods can be used to produced high quality approximations to a firm s technology unlike the local approximations provided by the conventional class of flexible functional forms seminonparametric methods generate global spans within large classes of functions however that approach usually spans a much larger space than the neoclassical function space relevant to most production modeling an exception is the asymptotically ideal model aim generated from the muntz szatz series expansion since every basis function in that expansion is within the neoclassical function space a straightforward method exists for imposing neoclassical regularity when all factors are substitutes since the relevant constraints are inequality restrictions we implement the approach using bayesian methods to avoid the problems of sampling distribution truncation that would occur from sampling theoretic methods we further discuss the relevant extensions that would permit complementary factors nonconstant returns to scale and technological change

fourier encoding of closed planar boundaries a circular gaussian autoregressive cgar source is used as a model for closed planar curves a class of suboptimal encoding schemes is considered which separately quantize the fourier coefficients of the boundary application of rate distortion theoretic techniques leads to parametric equations describing the optimal encoding bound interpretation of these equations establishes a sampling criterion and a computationally efficient transform encoding scheme for the suboptimal class several variants of this transform encoding scheme are suggested and compared to the encoding bound

on deviations between neoclassical and gft based true cost of living indexes derived from the same demand function system abstract given that a generalized fechner thurstone gft direct utility function and a neoclassical direct utility function yield exactly the same system of demand functions then for which combinations of a regions of the domain of neoclassical parameters and b price and total expenditure regimes do the alternative true cost of living indexes tcli s and their sensitivities to changes in casual factors differ significantly practical neoclassical alternatives to the gft based non parametric tcli s are limited to parametric tcli s based on the class of implicit utility models discussed by barnett this paper describes the design and results of a simulation experiment which generated alternative tcli s under different parameter specifications focus of appraisal is on specifications which produced realistic demand elasticities and large deviations between tcli s

stochastic models for closed boundary analysis representation and reconstruction the analysis of closed boundaries of arbitrary shapes on a plane is discussed specifically the problems of representation and reconstruction are considered a one to one correspondence between the given closed boundary and a univariate or multivariate sequence of real numbers is set up univariate or multivariate circular autoregressive models are suggested for the representation of the sequence of numbers derived from the closed boundary the stochastic model representing the closed boundary is invariant to transformations like sealing translation choice of starting point and rotation over angles that are multiples of 2 pi n where n is the number of observations methods for estimating the unknown parameters of the model are given and a decision rule for choosing the appropriate number of coefficients is included constraints on the estimates are derived so that the estimates are invariant to the transformations of the boundaries the stochastic model enables the reconstruction of a dosed boundary using fft algorithms results of simulations are included and the application to contour coding is discussed

the global properties of the minflex laurent generalized leontief and translog flexible functional forms caves and christensen 16 have provided a procedure for displaying the regular regions of a flexible functional form in the 2 good homothetic and nonhomothetic cases and in the 3 good homothetic case we extend the procedure to the nonhomothetic 3 good case and we apply the extended procedure to the translog generalized leontief and minflex laurent flexible functional forms in addition we acquire the regular regions for the minflex laurent model in the 2 good nonhomothetic case and superimpose the resulting regions on those already found by caves and christensen for the translog and generalized leontief models we find that the new minflex laurent model generally has the largest regular regions of the three fiexible functional forms in addition the regular region of the minflex laurent model is found to expand as real income increases as a result that model is particularly well suited for use with time series data which typically is characterized by positive long term growth trends in real income in such applications all recent data and future forecasts can be expected to lie within the regular region of the minflex laurent model although it is possible for some of the earliest data to fall outside that regular region the model s regular region nevertheless is sufficiently large to hold even all of those earliest data points in many data sets the regular region of each of three models moves when the model s parameters are changed with the generalized leontief or translog model the regular region s shape location and size are unpredictable without prior knowledge of the model s parameters with either of those two models the intersection of the model s regular regions as the parameters are changed is contained within a very small neighborhood of the one point at which we require the model to be regular with the minflex laurent model the primary properties of the regular regions are invariant to the values of the parameters and the intersection of the displayed regular regions is a very large unbounded set the width of that intersection increases without limit as real income increases

review of shape representation and description techniques more and more images have been generated in digital form around the world there is a growing interest in 1nding images in large collections or from remote databases in order to 1nd an image the image has to be described or represented by certain features shape is an important visual feature of an image searching for images using shape features has attracted much attention there are many shape representation anddescription techniques in the literature in this paper we classify and review these important techniques we examine implementation procedures for each technique and discuss its advantages and disadvantages some recent research results are also included and discussed in this paper finally we identify some promising techniques for image retrieval according to standard principles

foncteurs d ensembles munis d une double action resume sommaire 1 introduction 2 notations generalites 3 ensembles munis d une double action 3 1 notations 3 2 formule de mackey 3 3 decomposition d un morphisme 3 4 sous categories 3 4 1 ensembles p q libres 3 4 2 groupes reductifs 4 foncteurs simples 5 une theorie de vortex et de source 6 une seconde theorie de vortex et source 7 le foncteur de burnside 7 1 un homomorphisme deb g dans end g 7 2 les sous foncteurs du foncteur de burnside en caracteristique 0 7 2 1 premier exemple 7 2 2 les constantesmg n 7 2 3 lesb groupes 7 2 4 les sous foncteurs deb 7 2 5 exemples deb groupes 8 exemples de foncteurs simples 8 1 le cas des foncteurs de mackey globaux 8 2 les foncteurssh k 8 3 certains foncteurs simples en caracteristique 0 9 l algebreegg end g egg 9 1 une base naturelle 9 2 multiplication 9 3 semi simplicite 10 le foncteur des representations complexes 10 1 caracteres 10 2 sous foncteurs et decomposition 10 3 semi simplicite

maximum entropy estimation of density and regression functions abstract this paper presents an information efficient technique to determine the functional forms of density and regression functions by maximizing entropy subject to given side conditions a flexible functional form approach is established as special cases of this approach exponential polynomial cobb douglas translog generalized cobb douglas generalized leontief fourier flexible form and minflex laurent series etc can be derived in a monte carlo experiment the maximum entropy regression method shows good performance in terms of goodness of fit boxplots and isoquants produced by the maximum entropy method are compared with those produced by other well known functions

an experimental comparison of autoregressive and fourier based descriptors in 2d shape classification an experimental comparison of shape classification methods based on autoregressive modeling and fourier descriptors of closed contours is carried out the performance is evaluated using two independent sets of data images of letters and airplanes silhouette contours are extracted from non occluded 2d objects rotated scaled and translated in 3d space several versions of both types of methods are implemented and tested systematically the comparison clearly shows better performance of fourier based methods especially for images containing noise

shape classification using invariant features and contextual information in the bag of words model in this paper we describe a classification framework for binary shapes that have scale rotation and strong viewpoint variations to this end we develop several novel techniques first we employ the spectral magnitude of log polar transform as a local feature in the bag of words model second we incorporate contextual information in the bag of words model using a novel method to extract bi grams from the spatial co occurrence matrix third a novel metric termed weighted gain ratio is proposed to select a suitable codebook size in the bag of words model the proposed metric is generic and hence it can be used for any clustering quality evaluation task fourth a joint learning framework is proposed to learn features in a data driven manner and thus avoid manual fine tuning of the model parameters we test our shape classification system on the animal shapes dataset and significantly outperform state of the art methods in the literature highlightsa shape classifier tolerant to scale rotation and viewpoint changes is proposed the inclusion of the histogram of bi grams improves the bag of words model codebook selection and feature learning improve the classification accuracy we report best results on the animal shapes dataset using the proposed method

a bivariate autoregressive technique for analysis and classification of planar shapes a bivariate autoregressive model is introduced for the analysis and classification of closed planar shapes the boundary coordinate sequence of a digitized binary image is sampled to produce a polygonal approximation to an object s shape this circular sample sequence is then represented by a vector autoregressive difference equation which models the individual cartesian coordinate sequences as well as coordinate interdependencies several classification features which are functions or transformations of the estimated coefficient matrices and the associated residual error covariance matrices are developed these features are shown to be invariant to object transformations such as translation rotation and scaling laboratory experiments involving object sets representative of industrial shapes are presented superior classification results are demonstrated

classification of partial 2 d shapes using fourier descriptors we present a method for the classification of 2 d partial shapes using fourier descriptors we formulate the problem as one of estimating the fourier descriptors of the unknown complete shape from the observations derived from an arbitrarily rotated and scaled shape with missing segments the method used for obtaining the estimates of the fourier descriptors minimizes a sum of two terms the first term of which is a least square fit to the given data subject to the condition that the number of missing boundary points is not known and the second term is the perimeter2 area of the unknown shape experiments with synthetic and real boundaries show that estimates closer to the true values of fourier descriptors of complete boundaries are obtained also classification experiments performed using real boundaries indicate that reasonable classification accuracies are obtained even when 20 30 percent of the data is missing

the global properties of the two minflex laurent flexible functional forms abstract the minflex laurent flexible functional form is a special case of a second order laurent series expansion the minflex laurent when constructed in square roots is called the minflex laurent ml generalized leontief the minflex laurent ml translog model is the minflex laurent in logarithms we find that the regular region of the ml translog is most often even larger than that of the ml generalized leontief model except when substitutability is very low we previously have shown that the regular region of the ml generalized leontief is substantially larger than that of the usual translog and generalized leontief models

the three dimensional global properties of the minflex laurent generalized leontief and translog flexible functional forms abstract we use the caves and christensen procedure to produce the regular regions of three flexible functional forms generalized leontief translog and barnett s new minflexlaurent model we display the regular regions in six cases with three goods using both three dimensional color graphics and two dimensional sections we find that minflex laurent generally has the largest regular region in addition the regular regions of that model are the most stable in shape across the six cases and always expand as real income increases consequently that model is especially well suited for use with income trended time series data

calculating geometric properties from fourier representation abstract the area the location of the centroid and the second order moments of a region are determined and expressed in closed form in terms of the fourier coefficients of its boundary function the orientation of the central axes and the second order central moments can then be easily obtained bounds on the perimeter of the region are derived in terms of the fourier coefficients as well

the minflex laurent translog flexible functional form abstract barnett s minflex laurent generalized leontief model was produced from a special case of a second order laurent series expansion in the square roots in this paper we produce a minflex laurent translog flexible functional form by the analogous expansion in the logarithms we prove that the model s regular region always grows monotonically as real income increases as a result the model is especially well suited for use with income trended time series data we also prove that the model satisfies diewert s definition of a flexible functional form and is no more deeply parameterized than is necessary to satisfy the flexibility criterion

the ideals of the slice burnside p biset functor abstract let g be a finite group and k be a field of characteristic zero our purpose is to investigate the ideals of the slice burnside functor k it turns out that they are the subfunctors f of k such that for any finite group g the evaluation f g is an ideal of the algebra k g this allows for a determination of the full lattice of ideals of the slice burnside p biset functor k p

the group of endo permutation modules the group d p of all endo permutation modules for a finite p group p is a finitely generated abelian group we prove that its torsion free rank is equal to the number of conjugacy classes of non cyclic subgroups of p we also obtain partial results on its torsion subgroup we determine next the structure of q otimes d viewed as a functor which turns out to be a simple functor s e q indexed by the elementary group e of order p 2 and the trivial out e module q finally we describe a rather strange exact sequence relating q otimes d p q otimes b p and q otimes r p where b p is the burnside ring and r p is the grothendieck ring of qp modules

fourier coding of image boundaries a transform coding scheme for closed image boundaries on a plane is described the given boundary is approximated by a series of straight line segments depending on the shape the boundary is represented by the x y coordinates of the endpoints of the line segments or by the magnitude of the successive radii vectors that are equispaced in angle around the given boundary due to the circularity present in the data the discrete fourier transform is used to exactly decorrelate the finite boundary data by fitting a gaussian circular autoregressive model to represent the boundary data estimates of the variances of the fourier coefficients are obtained using the variances of the fourier coefficients and the max quantizer the coding scheme is implemented the scheme is illustrated by an example

further thoughts on testing for causality with econometric models abstract the ontological basis for causality testing must be some empirically interpretable system leading one to specify a logically valid a priori law that can be shown to exist such paradigms as conventional linear and non linear models be they structural or time series tend to embody contradictory assumptions that unfortunately make causal interpretability problematic the paper demonstrates how these difficulties can be avoided using a stochastic coefficient approach the final part of this article is devoted to a discussion of probabilistic logic as a valid tool for scientific analysis and interpretation of causal relationships