scholarly journals On the Ricardian invariable measure of value in general convex economies

2019 ◽  
Vol 51 ◽  
pp. 539-549
Author(s):  
Kazuhiro Kurose ◽  
Naoki Yoshihara
Keyword(s):  
General Convex

scholarly journals Generalized principal eigenvalues of convex nonlinear elliptic operators in ℝN

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Anup Biswas ◽  
Prasun Roychowdhury
Keyword(s):  
Eigenvalue Problem ◽  
Principal Eigenvalue ◽  
Unbounded Domains ◽  
Elliptic Operators ◽  
Maximum Principles ◽  
Generalized Eigenvalues ◽  
Nonlinear Elliptic ◽  
Generalized Eigenvalue ◽  
General Convex ◽  
Appl Math

AbstractWe study the generalized eigenvalue problem in {\mathbb{R}^{N}} for a general convex nonlinear elliptic operator which is locally elliptic and positively 1-homogeneous. Generalizing [H. Berestycki and L. Rossi, Generalizations and properties of the principal eigenvalue of elliptic operators in unbounded domains, Comm. Pure Appl. Math. 68 2015, 6, 1014–1065], we consider three different notions of generalized eigenvalues and compare them. We also discuss the maximum principles and uniqueness of principal eigenfunctions.

scholarly journals Higher order strongly general convex functions and variational inequalities

2020 ◽  
Vol 5 (4) ◽  
pp. 3646-3663 ◽  
Author(s):  
Muhammad Aslam Noor ◽  
◽  
Khalida Inayat Noor
Keyword(s):  
Variational Inequalities ◽  
Convex Functions ◽  
Higher Order ◽  
General Convex

An n-Vertex Theorem for Convex Space Curves

1985 ◽  
Vol 37 (2) ◽  
pp. 217-237
Author(s):  
Tibor Bisztriczky
Keyword(s):  
Topological Space ◽  
Euclidean Plane ◽  
Convex Surface ◽  
Space Curves ◽  
Straight Line ◽  
History Of ◽  
General Convex ◽  
Vertex Theorem ◽  
The Subject ◽  
Three Space

The classical four-vertex theorem states that a simple closed convex C2 curve in the Euclidean plane has at least four vertices (points of extreme curvature). This theorem has many generalizations with regard to both the curve and the topological space and for a history of the subject, we refer to [4] and [1]. The particular generalization of concern, credited to H. Mohrmann, is the following n-vertex theorem.Let a simple closed C3 curve on a closed convex surface be intersected by a suitable plane in n points. Then the curve has at least n inflections (vertices).The closed convex surface in the preceding is defined as having at most two points in common with any straight line. Presently, we extend this result to curves on more general convex surfaces in a real projective three-space P3.

VOFTools 3.2: Added VOF functionality to initialize the liquid volume fraction in general convex cells

2019 ◽  
Vol 245 ◽  
pp. 106859
Author(s):  
Joaquín López ◽  
Julio Hernández ◽  
Pablo Gómez ◽  
Claudio Zanzi ◽  
Rosendo Zamora
Keyword(s):  
Volume Fraction ◽  
Liquid Volume ◽  
Liquid Volume Fraction ◽  
General Convex

Asymptotic Formulae for the Lattice Point Enumerator

1999 ◽  
Vol 51 (2) ◽  
pp. 225-249 ◽  
Author(s):  
U. Betke ◽  
K. Böröczky
Keyword(s):  
Convex Body ◽  
Surface Area ◽  
Positive Curvature ◽  
Convex Bodies ◽  
Mixed Volume ◽  
Lattice Points ◽  
Asymptotic Formulae ◽  
General Convex ◽  
Lattice Surface ◽  
Small Deformations

AbstractLet M be a convex body such that the boundary has positive curvature. Then by a well developed theory dating back to Landau and Hlawka for large λ the number of lattice points in λM is given by G(λM) = V(λM) + O(λd−1−ε(d)) for some positive ε(d). Here we give for general convex bodies the weaker estimatewhere SZd (M) denotes the lattice surface area of M. The term SZd is optimal for all convex bodies and o(λd−1) cannot be improved in general. We prove that the same estimate even holds if we allow small deformations of M.Further we deal with families {Pλ} of convex bodies where the only condition is that the inradius tends to infinity. Here we havewhere the convex body K satisfies some simple condition, V(Pλ; K; 1) is some mixed volume and S(Pλ) is the surface area of Pλ.

Stable Lattices

1953 ◽  
Vol 5 ◽  
pp. 261-270 ◽  
Author(s):  
Harvey Cohn
Keyword(s):  
Convex Body ◽  
Finite Number ◽  
Quadratic Forms ◽  
Convex Bodies ◽  
Lattice Points ◽  
Three Dimensions ◽  
General Convex ◽  
Critical Lattice ◽  
The Absolute

The consideration of relative extrema to correspond to the absolute extremum which is the critical lattice has been going on for some time. As far back as 1873, Korkine and Zolotareff [6] worked with the ellipsoid in hyperspace (i.e., with quadratic forms), and later Minkowski [8] worked with a general convex body in two or three dimensions. They showed how to find critical lattices by selection from among a finite number of relative extrema. They were aided by the long-recognized premise that only a finite number of lattice points can enter into consideration [1] when one deals with lattices “admissible to convex bodies.”

scholarly journals General convex stochastic orderings and related martingale-type structures

2007 ◽  
Vol 39 (01) ◽  
pp. 105-127
Author(s):  
Francisco Vera ◽  
James Lynch
Keyword(s):  
Convex Functions ◽  
Joint Distribution ◽  
Model Fitting ◽  
Data Confidentiality ◽  
Generalized Convex Functions ◽  
Stochastic Orderings ◽  
Seminal Work ◽  
Comparison Of Experiments ◽  
Total Integral ◽  
General Convex

Blackwell (1951), in his seminal work on comparison of experiments, ordered two experiments using a dilation ordering: one experiment, Y, is ‘more spread out’ in the sense of dilation than another one, X, if E(c(Y))≥E(c(X)) for all convex functions c. He showed that this ordering is equivalent to two other orderings, namely (i) a total time on test ordering and (ii) a martingale relationship E(Yʹ | Xʹ)=Xʹ, where (Xʹ,Yʹ) has a joint distribution with the same marginals as X and Y. These comparisons are generalized to balayage orderings that are defined in terms of generalized convex functions. These balayage orderings are equivalent to (i) iterated total integral of survival orderings and (ii) martingale-type orderings which we refer to as k-mart orderings. These comparisons can arise naturally in model fitting and data confidentiality contexts.

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