Locally averaged risk

Summary A heuristic method of reducing a class of admissible or Bayes decision rules is given. A new risk function is defined which is called the locally averaged risk. Bayes and admissible rules with respect to the new risk function are calledG-Bayes andG-admissible, respectively. It is shown under general assumptions that the class ofG-Bayes decision rules is a subset of the class of Bayes decision rules and the class ofG-admissible decision rules is a subset of the class of admissible decision rules. Some examples are considered, showing that the usual estimates of the parameter of a distribution with squared error as loss function, which are known to be admissible, are alsoG-admissible. This work was supported in part by NASA Grant-NGR 15-003-064 and NSF Grant-GP 7496 at Indiana University.     

A structure for the Bayes analysis of the performance of detection systems with multiple sensors and sites

The usual Bayes analysis for optimum detection systems is extended to include the costs of equipment, location, maintenance, and other features of operation, in addition to the customary preassigned costs of correct and incorrect decisions, when multiple receiving sites (Q) and sensors (M) are employed for acquisition and ultimately joint processing of data for simple binary (i.e.,yes orno) decisions as to the presence or absence of a signal source. A risk formalism is constructed which indicates how the expected overall costs of both decision and operation can be generally determined for a variety of realistic cost models. Since the expected cost or average risk of decision is a monotonically decreasing function ofM andQ, while the associated costs of operation are reasonably described by monotonically increasing functions ofM andQ, values ofM andQ may also exist for which the total average cost (or risk) can be minimized, as well as the cost of decision itself (i.e., for a Bayes decision system). In any case, the physics of the particular detection situation (radar, radio, seismic, acoustic, etc.) is included in the usual way, under the important constraint of decision optimality (i.e., Bayes decision). Thus, one purpose of this introductory study is to provide some possible models for system evaluation and comparison which specifically include the often controlling factors of operational costs (vis-à-vis those of decision). A simple analytic example is used to illustrate the approach, which is, however, capable of handling much more general examples, both conceptually and quantitatively. In these more general cases, it is expected that computer aids will be needed.This work was supported by the United States Air Force, Project RAND, Contract No. F44620-67-C-0045.     

ψ-correct decision for selection and elimination

Summary The selection oft out ofk populations with parameters θ _i (i=1, ...,k) is said to result in an ψ-correct decision provided ψ (minimum selected θ)>maximum non-selected θ where ψ(θ) (>θ) is an increasing function. For the cases of location or scale parameters the minimum probability of ψ-correct decision over the entire parameter space is shown to be no less than the minimum probability of correct selection over a preference zone determined by ψ(θ). For other types of parameters this result is shown to be true under certain conditions linking the distribution function and the ψ function.     

On the empirical Bayes approach to multiple decision problems with sequential components

The empirical Bayes approach to multiple decision problems with a sequential decision problem as the component is studied. An empirical Bayesm-truncated sequential decision procedure is exhibited for general multiple decision problems. With a sequential component, an empirical Bayes sequential decision procedure selects both a stopping rule function and a terminal decision rule function for use in the component. Asymptotic results are presented for the convergence of the Bayes risk of the empirical Bayes sequential decision procedure.     

On existence of sets of distinct representatives for families of subsets of a multiset

IfX is a family ofl-subsets of a multiset, then there is a set of distinct representatives of the members ofX among the (l-k)-subsets of the members ofX provided the cardinality ofX does not exceed a certain bound. An algorithm for calculating this bound is given.     

On zero-degree stochastic geometric programs

The Mellin transform is used to encode randomness in the constraint and objective function coefficients using the substituted dual function. This enables one to obtain statistical moments and the probability distribution of the optimal objective valueZ*. Advantage is taken of the form of the dual function and the limiting property of the lognormal distribution to prove that the probability distribution ofZ* approximates the lognormal distribution, independent of the distribution of the parameters. This is of importance because those probability distributions are seldom known; even if they are, a derivation of the distribution ofZ* is apt to be elusive. Further, the larger the number of stochastic parameters in the geometric program, the more closely, in general, does the distribution ofZ* approximate the lognormal distribution. Illustrative examples are provided.Credit is due to Keith R. Weiss who developed the examples. The Office of Naval Research supported the work under Contract No. N000-14-75-C-0254.     

Consistency of Posterior Mixtures in the Gaussian Family on a Hilbert Space and Its Applications

Majumdar (1994, J. Multivariate Anal.48 87-105) compounds (in the sense of Robbins, 1951, "Proceedings, Second Berkeley Sympos. Math. Statist. Probab.," pp. 131-148, Univ. of California Press, Berkeley) the estimation problem in the mean-parameter family of Gaussian distributions on a real separable infinite dimensional Hilbert space. The question of asymptotic optimality of compound estimators that are Bayes versus a hyperprior mixture of i.i.d. priors on the compound parameter is reduced there, under a compactness restriction on the parameter space, to the question of consistency, in an extended sense, of a certain posterior mixture for the empirical mixture. For mixing hyperpriors with full topological support, that consistency result is obtained in this paper. A corollary of the consistency result is applied to obtain asymptotically optimal decision rules in the empirical Bayes problem involving the mean-parameter Gaussian family and a sufficiently smooth risk function.     

Linear problem of tracking a given motion under an integral constraint on control

We consider the problem of optimally tracking a given vector function by means of a generalized projection of the trajectory of a linear controlled object with an integral constraint on the control. The deviation from a given motion is measured in the metric of the space C ^m [0, T] of continuous vector functions of appropriate dimension m. We describe a constructive method for solving this optimization problem with a given accuracy.     

The Jacobian of a nonorientable Klein surface

Using divisors, an analog of the Jacobian for a compact connected nonorientable Klein surfaceY is constructed. The Jacobian is identified with the dual of the space of all harmonic real one-forms onY quotiented by the torsion-free part of the first integral homology ofY. Denote byX the double cover ofY given by orientation. The Jacobian ofY is identified with the space of all degree zero holomorphic line bundlesL overX with the property thatL is isomorphic to σ*/-L, where σ is the involution ofX.     

The classical decision problem and partial functions

We consider the decision problem for sets of sentences of first-order logic when instead of interpreting function symbols as total functions over the universe of a model (henceforth referred to as the usual interpretation) we interpret them as partial functions.We consider only standard classes, which are certain sets of prenex sentences specified by restrictions on the prefix and on the numbers ofk-place predicate and function symbols for eachk1. Standard classes are introduced in [1] and it is proved there that the decision problem for any set of prenex sentences specified by such restrictions reduces to that for the standard classes.We solve the decision problem completely for standard classes with at least one function symbol and both with and without equality.This problem was suggested to me by my supervisor, Professor Yuri Gurevich who was confident that the results would be very similar to those for the usual interpretation and could be achieved by similar techniques.     

An approximation of feasible sets in semi-infinite optimization

The paper deals with the feasible setM of a semi-infinite optimization problem, i.e.M is a subset of the finite-dimensional Euclidean space and is basically defined by infinitely many inequality constraints. Assuming that the extended Mangasarian-Fromovitz constraint qualification holds at all points fromM, it is shown that the quadratic distance function with respect toM is continuously differentiable on an open neighborhood ofM. If, in addition,M is compact, then the set , which is described by this quadratic distance function, is shown to be an appropriate approximation ofM and the setsM and can be topologically identified via a homeomorphism.     

The Dirichlet problem of a discontinuous Markov process

Given a Markov process satisfying certain general type conditions, whose paths are not assumed to be continuous. LetD be an open subset of the state spaceE. Any bounded function defined on the complement ofD extends to be a function onE such that it is harmonic inD and satisfies the Dirichlet boundary condition at any regular boundary point ofD. The relation between harmonic functions and the characteristic operator of the given process is discussed.     

On the size of balls covered by analytic transformations

Two quantitative forms of the inverse function theorem giving estimates on the size of balls covered biholomorphically are proved for holomorphic mappings of a ball in a Banach space into the space. Also, a Bloch theorem forK-quasiconformal mappings on the open unit ball of a Banach space is given and some mapping properties ofK-quasiconformal mappings are deduced.Research supported by N. S. F. Grant GP-33117A-2.     

Relations between the support of a compactly supported function and the exponential-polynomials spanned by its integer translates

The interrelation between the shape of the support of a compactly supported function and the space of all exponential-polynomials spanned by its integer translates is examined. The results obtained are in terms of the behavior of these exponential-polynomials on certain finite subsets ofZ ^s , which are determined by the support of the given function. Several applications are discussed. Among these is the construction of quasi-interpolants of minimal support and the construction of a piecewise-polynomial whose integer translates span a polynomial space which is not scale-invariant. As to polynomial box splines, it is proved here that in many cases a polynomial box spline admits a certain optimality condition concerning the space of the total degree polynomials spanned by its integer translates: This space is maximal compared with the spaces corresponding to other functions with the same supportCommunicated by Klaus Höllig.     

Asymptotic Limit of the Bayes Actions Set Derived from a Class of Loss Functions

Similarly to the determination of a prior in Bayesian Decision theory, an arbitrarily precise determination of the loss function is unrealistic. Thus, analogously to global robustness with respect to the prior, one can consider a set of loss functions to describe the imprecise preferences of the decision maker. In this paper, we investigate the asymptotic behavior of the Bayes actions set derived from a class of loss functions. When the collection of additional observations induces a decrease in the range of the Bayes actions, robustness is improved. We give sufficient conditions for the convergence of the Bayes actions set with respect to the Hausdorff metric and we also give the limit set. Finally, we show that these conditions are satisfied when the set of decisions and the set of states of nature are subsets of ^p.     

Optimization of a time-variable,constrained control matrix

The problem posed is to choose, in a optimal manner, a time-variable, bounded, linear transformation defining the velocity of a state point inn-dimensional space in terms of the state. The two-point boundary-value problem which arises from an application of the Pontryagin maximum principle is explicitly solvable; hence, a formula is derived showing that the optimal trajectories in state space are equiangular spirals in two-dimensional subspaces ofR ⁿ and also describing the boundary of the set of attainability. This formula is used to solve the problem of minimal-time transfer between any two given points, and the optimal control is specified both as an open-loop and a closed-loop controller. The solutions to the problem of maximizing a linear payoff function of the final state and of maximizing the angle of rotation of the state vector about the origin are also given.     

Numerical decomposition of a convex function

Given then×p orthogonal matrixA and the convex functionf:R ⁿR, we find two orthogonal matricesP andQ such thatf is almost constant on the convex hull of ± the columns ofP, f is sufficiently nonconstant on the column space ofQ, and the column spaces ofP andQ provide an orthogonal direct sum decomposition of the column space ofA. This provides a numerically stable algorithm for calculating the cone of directions of constancy, at a pointx, of a convex function. Applications to convex programming are discussed.This work was supported by the National Science and Engineering Research Council of Canada (Grant No. A3388 and Summer Grant).     

Penalty methods for mathematical programming inE nwith general constraint sets

This paper extends the principal supporting results and the general convergence theorems for penalty methods, obtained by Fiacco and McCormick (Ref. 1) for the continuous mathematical programming problem, to the problem of minimizing a mildly regulated objective function over any nonempty subset ofE ⁿ.The constraint set need not be defined through a collection of inequalities. A general auxiliary function is defined, and the desired minimizing sequence is shown to exist, without additional assumptions (i.e., assumptions other than those invoked in the principal convergence theorem of Ref. 1). A particularly interesting consequence is the fact that a discrete (e.g., integer) programming problem can be solved by asingle unconstrained minimization of the auxiliary function.     

Necessary optimality conditions for a class of nonsmooth vector optimization

The Kuhn-Tucker type necessary conditions of weak efficiency are given for the problem of minimizing a vector function whose each component is the sum of a differentiable function and a convex function, subject to a set of differentiable nonlinear inequalities on a convex subset C of ℝ ⁿ , under the conditions similar to the Abadie constraint qualification, or the Kuhn-Tucker constraint qualification, or the Arrow-Hurwicz-Uzawa constraint qualification. Supported by the National Natural Science Foundation of China (No. 70671064, No. 60673177), the Province Natural Science Foundation of Zhejiang (No.Y7080184) and the Education Department Foundation of Zhejiang Province (No. 20070306).     

Über gewisseG-stabile Teilmengen in projektiven Räumen

LetG be a connected affine algebraic group over an algebraically closed field of characteristic 0. LetN be a regularG-module andP(N) its projective space. In this article we study those locally closedG-stable subsets ofP(N) which contain in everyG-orbit a fixed point of a maximal unipotent subgroup ofG. Varieties of this type which contain only one closed orbit are classified by “painted monoids”. Necessary and sufficient conditions on a painted monoid are given so that the corresponding variety is smooth.