Absolutely continuous invariant measures for random maps with position dependent probabilities

A random map is discrete-time dynamical system in which one of a number of transformations is randomly selected and applied at each iteration of the process. Usually the map τ_k is chosen from a finite collection of maps with constant probability p_k. In this note we allow the p_k's to be functions of position. In this case, the random map cannot be considered to be a skew product. The main result provides a sufficient condition for the existence of an absolutely continuous invariant measure for position dependent random maps on [0,1]. Geometrical and topological properties of sets of absolutely continuous invariant measures, attainable by means of position dependent random maps, are studied theoretically and numerically.     

A linear regression model for imprecise response

A linear regression model with imprecise response and p real explanatory variables is analyzed. The imprecision of the response variable is functionally described by means of certain kinds of fuzzy sets, the LR fuzzy sets. The LR fuzzy random variables are introduced to model usual random experiments when the characteristic observed on each result can be described with fuzzy numbers of a particular class, determined by 3 random values: the center, the left spread and the right spread. In fact, these constitute a natural generalization of the interval data. To deal with the estimation problem the space of the LR fuzzy numbers is proved to be isometric to a closed and convex cone of R³ with respect to a generalization of the most used metric for LR fuzzy numbers. The expression of the estimators in terms of moments is established, their limit distribution and asymptotic properties are analyzed and applied to the determination of confidence regions and hypothesis testing procedures. The results are illustrated by means of some case-studies.     

Countable Random Sets: Uniqueness in Law and Constructiveness

The first part of this article deals with theorems on uniqueness in law for σ-finite and constructive countable random sets, which in contrast to the usual assumptions may have points of accumulation. We discuss and compare two approaches on uniqueness theorems: first, the study of generators for σ-fields used in this context and, secondly, the analysis of hitting functions. The last section of this paper deals with the notion of constructiveness. We prove a measurable selection theorem and a decomposition theorem for constructive countable random sets, and study constructive countable random sets with independent increments.     

Index sets in the arithmetical Hierarchy

We prove the following results: every recursively enumerable set approximated by finite sets of some set M of recursively enumerable sets with index set in π₂ is an element of M, provided that the finite sets in M are canonically enumerable. If both the finite sets in M and in M̄ are canonically enumerable, then the index set of M is in σ₂∩π₂ if and only if M consists exactly of the sets approximated by finite sets of M and the complement M̄ consists exactly of the sets approximated by finite sets of M̄. Under the same condition M or M̄ has a non-empty subset with recursively enumerable index set, if the index set of M is in σ₂∩π₂.If the finite sets in M are canonically enumerable, then the following three statements are equivalent: (i) the index set of M is in σ₂\π₂, (ii) the index set of M is σ₂-complete, (iii) the index set of M is in σ₂ and some sequence of finite sets in M approximate a set in M̄.Finally, for every n ⩾ 2, an index set in σ_n \ π_n is presented which is not σ_n-complete.     

Connected domination of regular graphs

A dominating setD of a graph G is a subset of V(G) such that for every vertex v∈V(G), either v∈D or there exists a vertex u∈D that is adjacent to v in G. Dominating sets of small cardinality are of interest. A connected dominating setC of a graph G is a dominating set of G such that the subgraph induced by the vertices of C in G is connected. A weakly-connected dominating setW of a graph G is a dominating set of G such that the subgraph consisting of V(G) and all edges incident with vertices in W is connected. In this paper we present several algorithms for finding small connected dominating sets and small weakly-connected dominating sets of regular graphs. We analyse the average-case performance of these heuristics on random regular graphs using differential equations, thus giving upper bounds on the size of a smallest connected dominating set and the size of a smallest weakly-connected dominating set of random regular graphs.     

Gaussian random measures

A Gaussian random measure is a mean zero Gaussian process η(A), indexed by sets A in a σ-field, such that η(ΣA_i)=Ση(A_i), where ΣA_i indicates disjoint union and the series on the right is required to converge everywhere, so η is a random signed measure. (This is in contrast to so-called second order random measures, which only require quadratic mean convergence.) The covariance kernel of η is the signed bimeasure ν₀(A,B)=Eη(A)η(B). We give a characterization of those bimeasures which are covariance kernels of Gaussian random measures, and we show that every Gaussian random measure has an exponentially integrable total variation and is a.s. absolutely continuous with respect to a fixed finite measure on the state space.     

On maximum tests for normal distributions

Lety be a normally distributed random vector with known regular covariance matrix and letA, B be disjoint closed convex sets inR ⁿ . To be tested is the zero-hypothesisE(y)εA against the alternative hypothesisE(y) ε B at a level of significanceα. Taking the set of admissible tests as one strategy set, the set of probability densities corresponding toB as the other strategy set and the power function of the test problem as the pay-off function this game has an equilibrium point. Thus there is a test, in particular a Neyman-Pearson test, which is simultaneously a maximin and a minimax test. The optimal test is uniquely determined, except on sets with measure zero. Finally the case of non-convexA, B is briefly considered.     

A general theory of some positive dependence notions

A general theory of concepts of positive dependence, which are weaker than association but stronger than orthant dependence, is developed. A random vector X is associated if and only if $\text{P(}\text{X}\text{∈ A ? B) ≥ P(}\text{X}\text{∈ A) P(}\text{X}\text{∈ B)}$ for all open upper sets A and B. By requiring the above inequality to hold only for some open upper sets A and B various notions of positive dependence which are weaker than association are obtained. First a general theory is given and then the results are specialized to some concepts of a particular interest. Various properties and interrelationships are derived and some applications are discussed.     

Point Sets on the Sphere \mathbb{S}^{2} with Small Spherical Cap Discrepancy

In this paper we study the geometric discrepancy of explicit constructions of uniformly distributed points on the two-dimensional unit sphere. We show that the spherical cap discrepancy of random point sets, of spherical digital nets and of spherical Fibonacci lattices converges with order?N ^?1/2. Such point sets are therefore useful for numerical integration and other computational simulations. The proof uses an area-preserving Lambert map. A?detailed analysis of the level curves and sets of the pre-images of spherical caps under this map is given.     

A new family of convex weakly compact valued random variables in Banach space and applications to laws of large numbers

We consider a new family of convex weakly compact valued integrable random sets which is called an adapted array of convex weakly compact valued integrable random variables of type p (1?p?2). By this concept, more general laws of large numbers will be established. Some illustrative examples are provided.     

On Random Marked Sets with a Smaller Integer Dimension

The paper deals with random marked sets in ${\mathbb R}^d$ which have integer dimension smaller than d. Statistical analysis is developed which involves the random-field model test and estimation of first and second-order characteristics. Special models are presented based on tessellations and solutions of stochastic differential equations (SDE). The simulation of these sets makes use of marking by means of Gaussian random fields. A space-time nature of the model based on SDE is taken into account. Numerical results of the estimation and testing are discussed. Real data analysis from the materials research investigating a grain microstructure with disorientations of faces as marks is presented.     

Integration of combinatorial decompositions in the presence of collinearities

Many results in Combinatorial Integral Geometry are derived by integration of the combinatorial decompositions associated with finite point sets {P _i } given in the plane ?². However, most previous cases of integration of the decompositions in question were carried out for the point sets {P _i } containing no triads of collinear points, where the familiar algorithm sometimes called the “Four indicator formula” can be used. The present paper is to demonstrate that the complete combinatorial algorithm valid for sets {P _i } not subject to the mentioned restriction opens the path to various results, including the field of Stochastic Geometry. In the paper the complete algorithm is applied first in an integration procedure in a study of the perforated convex domains, i.e convex domains containing a finite array of non-overlapping convex holes. The second application is in the study of random colorings of the plane that are Euclidean motions invariant in distribution, basing on the theory of random polygonal windows from the so-called Independent Angles (IA) class. The method is a direct averaging of the complete combinatorial decompositions written for colorings observed in polygonal windows from the IA class. The approach seems to be quite general, but promises to be especially effective for the random coloring generated by random Poisson polygon process governed by the Haar measure on the group of Euclidean motions of the plane, assuming that a point P ∈ ?² is colored J if P is covered by exactly J polygons of the Poisson process. A general theorem clearing the way for Laplace transform treatment of the random colorings induced on line segments is formulated.     

Level sets of the Takagi function: local level sets

The Takagi function ??: [0,1] ?? [0, 1] is a continuous non-differentiable function constructed by Takagi in 1903. The level sets L(y)?=?{x : ??(x)?=?y} of the Takagi function ??(x) are studied by introducing a notion of local level set into which level sets are partitioned. Local level sets are simple to analyze, reducing questions to understanding the relation of level sets to local level sets, which is more complicated. It is known that for a ??generic?? full Lebesgue measure set of ordinates y, the level sets are finite sets. In contrast, here it is shown for a ??generic?? full Lebesgue measure set of abscissas x, the level set L(??(x)) is uncountable. An interesting singular monotone function is constructed associated to local level sets, and is used to show the expected number of local level sets at a random level y is exactly ${\frac{3}{2}}$ .     

Complete separation in the random and Cohen models

It is shown that in the model obtained by adding κ many random reals, where κ is a supercompact cardinal, every C^?-embedded subset of a first countable space (even with character smaller than κ) is C-embedded. It is also proved that if two ground model sets are completely separated after adding a random real then they were completely separated originally but CH implies that the Cohen poset does not have this property.     

Random sets of finite perimeter

An approach to modelling random sets with locally finite perimeter as random elements in the corresponding subspace of L¹ functions is suggested. A Crofton formula for flat sections of the perimeter is shown. Finally, random processes of particles with finite perimeter are introduced and it is shown that their union sets are random sets with locally finite perimeter.     

Iterated Boolean random varieties and application to fracture statistics models

Models of random sets and of point processes are introduced to simulate some specific clustering of points, namely on random lines in R² and R³ and on random planes in R³. The corresponding point processes are special cases of Cox processes. The generating distribution function of the probability distribution of the number of points in a convex set K and the Choquet capacity T (K) are given. A possible application is to model point defects in materials with some degree of alignment. Theoretical results on the probability of fracture of convex specimens in the framework of the weakest link assumption are derived, and used to compare geometrical effects on the sensitivity of materials to fracture.     

Modified Schmidt games and Diophantine approximation with weights

We show that the sets of weighted badly approximable vectors in Rn are winning sets of certain games, which are modifications of (α,β)-games introduced by W.M. Schmidt in 1966. The latter winning property is stable with respect to countable intersections, and is shown to imply full Hausdorff dimension.     

A jump-diffusion model for option pricing under fuzzy environments

Owing to fluctuations in the financial markets from time to time, the rate λ of Poisson process and jump sequence {V_i} in the Merton’s normal jump-diffusion model cannot be expected in a precise sense. Therefore, the fuzzy set theory proposed by Zadeh [Zadeh, L.A., 1965. Fuzzy sets. Inform. Control 8, 338-353] and the fuzzy random variable introduced by Kwakernaak [Kwakernaak, H., 1978. Fuzzy random variables I: Definitions and theorems. Inform. Sci. 15, 1-29] and Puri and Ralescu [Puri, M.L., Ralescu, D.A., 1986. Fuzzy random variables. J. Math. Anal. Appl. 114, 409-422] may be useful for modeling this kind of imprecise problem. In this paper, probability is applied to characterize the uncertainty as to whether jumps occur or not, and what the amplitudes are, while fuzziness is applied to characterize the uncertainty related to the exact number of jump times and the jump amplitudes, due to a lack of knowledge regarding financial markets. This paper presents a fuzzy normal jump-diffusion model for European option pricing, with uncertainty of both randomness and fuzziness in the jumps, which is a reasonable and a natural extension of the Merton [Merton, R.C., 1976. Option pricing when underlying stock returns are discontinuous. J. Financ. Econ. 3, 125-144] normal jump-diffusion model. Based on the crisp weighted possibilistic mean values of the fuzzy variables in fuzzy normal jump-diffusion model, we also obtain the crisp weighted possibilistic mean normal jump-diffusion model. Numerical analysis shows that the fuzzy normal jump-diffusion model and the crisp weighted possibilistic mean normal jump-diffusion model proposed in this paper are reasonable, and can be taken as reference pricing tools for financial investors.     

Disjoint dominating and total dominating sets in graphs

It has been shown [M.A. Henning, J. Southey, A note on graphs with disjoint dominating and total dominating sets, Ars Combin. 89 (2008) 159-162] that every connected graph with minimum degree at least two that is not a cycle on five vertices has a dominating set D and a total dominating set T which are disjoint. We characterize such graphs for which D∪T necessarily contains all vertices of the graph and that have no induced cycle on five vertices.     

Complexity of representation of graphs by set systems

Let $\text{F}$ be a family of subsets of S and let G be a graph with vertex set $\text{V={x}{}_{\mathrm{A}}\text{|A ∈}\text{F}\text{}}$ such that: (x_A, x_B) is an edge iff $\text{A?B≠}\text{0}\text{/}$. The family $\text{F}$ is called a set representation of the graph G.It is proved that the problem of finding minimum k such that G can be represented by a family of sets of cardinality at most k is NP-complete. Moreover, it is NP-complete to decide whether a graph can be represented by a family of distinct 3-element sets.The set representations of random graphs are also considered.