Asymptotic properties of a stochastic chemostat including species death rate

This paper deals with a stochastic system which models the population dynamics of a chemostat including species death rate. On the basis of the theory on Markov semigroup, we demonstrate that the probability densities of the distributions for the solutions are absolutely continuous. The densities will convergence in L¹ to an invariant density or weakly convergence to a singular measure under appropriate conditions. We also give the sufficient criteria for extinction exponentially of the species. To be specific, when D₁>D and the strength of perturbation is relatively small, we derive a precise threshold for the species survival.     

Sojourn and waiting times in a single-server system with state-dependent mean service rate

A birth-death queueing system with asingle server, first-come first-served discipline, Poisson arrivals and state-dependent mean service rate is considered. The problem of determining the equilibrium densities of the sojourn and waiting times is formulated, in general. The particular case in which the mean service rate has one of two values, depending on whether or not the number of customers in the system exceeds a prescribed threshold, is then investigated. A generating function is derived for the Laplace transforms of the densities of the sojourn and waiting times, leading to explicit expressions for these quantities. Explicit expressions for the second moments of the sojourn and waiting times are also obtained.     

A Lagrangian Approach for the Incompressible Navier‐Stokes Equations with Variable Density

We investigate the Cauchy problem for the inhomogeneous Navier‐Stokes equations in the whole n‐dimensional space. Under some smallness assumption on the data, we show the existence of global‐in‐time unique solutions in a critical functional framework. The initial density is required to belong to the multiplier space of \input amssym $\dot {B}^{n/p‐1}_{p,1}({\Bbb R}^n)$ . In particular, piecewise‐constant initial densities are admissible data provided the jump at the interface is small enough and generate global unique solutions with piecewise constant densities. Using Lagrangian coordinates is the key to our results, as it enables us to solve the system by means of the basic contraction mapping theorem. As a consequence, conditions for uniqueness are the same as for existence. © 2012 Wiley Periodicals, Inc.     

Time-dependent analysis of a queue with batch arrivals andn levels of nonpreemptive priority

A queueing system with batch arrivals andn classes of customers with nonpreemptive priorities between them is considered. Each batch arrives according to the Poisson distribution and contains customers of all classes while the service times follow arbitrary distributions with different probability density functions for each class. For such a model the system states probabilities both in the transient and in the steady state are analysed and also expressions for the Laplace transforms of the busy period densities for each class and for the general busy period are obtained.     

Asymptotic Behavior of Predator-Prey Systems Perturbed by White Noise

In this paper, we develop the results in Rudnicki (Stoch. Process. Appl. 108:93–107, 2003) to a stochastic predator-prey system where the random factor acts on the coefficients of environment. We show that there exists the density functions of the solutions and then, study the asymptotic behavior of these densities. It is proved that the densities either converges in L ¹ to an invariant density or converges weakly to a singular measure on the boundary.     

Optimal t-Edge-Robust r-Identifying Codes in the King Lattice

Locating faulty processors in a multiprocessor system gives a motivation for identifying codes. The concept of a t-edge-robust r-identifying code was introduced in [8]. We consider these codes in the king lattice and give several optimal densities. Research supported by the Academy of Finland under grants 207303 and 111940.     

Stable magnetic equilibria in collisionless plasmas

There are many steady states in collisionless plasmas. Their dynamical stability has been one of the main interests in the study of plasmas. In one-dimensional space, we discover some new types of stable equilibria by constructing new invariants to the Vlasov-Maxwell system. These stable equilibria include new flat-tail solutions that connect different densities, pressures, and strengths of constant magnetic fields at x = ±∞. © 1997 John Wiley & Sons, Inc.     

A Nonequilibrium Statistical Model of Spectrally Truncated Burgers‐Hopf Dynamics

Exact spectral truncations of the unforced, inviscid Burgers‐Hopf equation are Hamiltonian systems with many degrees of freedom that exhibit intrinsic stochasticity and coherent scaling behavior. For this reason recent studies have employed these systems as prototypes to test stochastic mode reduction strategies. In the present paper the Burgers‐Hopf dynamics truncated to n Fourier modes is treated by a new statistical model reduction technique, and a closed system of evolution equations for the mean values of the m lowest modes is derived for m ? n. In the reduced model the m‐mode macrostates are associated with trial probability densities on the phase space of the n‐mode microstates, and a cost functional is introduced to quantify the lack of fit of paths of these densities to the Liouville equation. The best‐fit macrodynamics is obtained by minimizing the cost functional over paths, and the equations governing the closure are then derived from Hamilton‐Jacobi theory. The resulting reduced equations have a fractional diffusion and modified nonlinear interactions, and the explicit form of both are determined up to a single closure parameter. The accuracy and range of validity of this nonequilibrium closure is assessed by comparison against direct numerical simulations of statistical ensembles, and the predicted behavior is found to be well represented by the reduced equations. © 2014 Wiley Periodicals, Inc.     

Hamiltonian structure of polynomial bundles

The Hamiltonian structure of nonlinear evolution equations for which the potentials of the Zakharov-Shabat system depend polynomially on a spectral parameter is investigated on the basis of a general group theoretic scheme. The orbits of the corresponding coadjoint action are calculated. Formulas for the generating functions of the densities and flows of conservation laws andM-operators are derived.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 123, pp. 67–76, 1983.     

On a version of the nonlinear equations of the nonlocal moment theory of plasticity of materials with mobile disclinations

Using the methods of nonequilibrium thermodynamics, continuum mechanics, differential geometry, and the continuous theory of disclinations, we obtain a closed system of differential equations that makes it possible to determine the unknown plastic fields, the defect densities connected with them, and the stresses caused in the body. The connection between the kinetic potentials and the load surface of the system is established.Translated fromMatematicheskie Metody i Fiziko-Mekhanicheskie Polya, Issue 35, 1992, pp. 62–69.     

The Markov moment problem and de Finetti’s theorem: Part II

This paper gives an abstract version of de Finettis theorem that characterizes mixing measures with L_p densities. The general setting is reviewed; after the theorem is proved, it is specialized to coin tossing and to exponential random variables. Laplace transforms of bounded densities are characterized, and inversion formulas are discussed.     

Approximating probability densities on the positive half-line

A variety of methods for approximating probability density functions on the positive half-line are presented and discussed. In particular, the method of moments and orthogonal expansion methods are studied. We give a new, computational proof that continuous probability densities vanishing at can be uniformly approximated by generalized hyper-exponential densities. The same denseness property is also shown to hold for families of densities expressible as sums of Erlang densitieswith common fixed rate parameter.This research was supported in part by Air Force Office of Scientific Research Contract F49620-86-C-0022.     

Copula-Type Estimators for Flexible Multivariate Density Modeling Using Mixtures

Copulas are popular as models for multivariate dependence because they allow the marginal densities and the joint dependence to be modeled separately. However, they usually require that the transformation from uniform marginals to the marginals of the joint dependence structure is known. This can only be done for a restricted set of copulas, for example, a normal copula. Our article introduces copula-type estimators for flexible multivariate density estimation which also allow the marginal densities to be modeled separately from the joint dependence, as in copula modeling, but overcomes the lack of flexibility of most popular copula estimators. An iterative scheme is proposed for estimating copula-type estimators and its usefulness is demonstrated through simulation and real examples. The joint dependence is modeled by mixture of normals and mixture of normal factor analyzer models, and mixture of t and mixture of t-factor analyzer models. We develop efficient variational Bayes algorithms for fitting these in which model selection is performed automatically. Based on these mixture models, we construct four classes of copula-type densities which are far more flexible than current popular copula densities, and outperform them in a simulated dataset and several real datasets. Supplementary material for this article is available online.     

Large sample inference from single server queues

Problems of large sample estimation and tests for the parameters in a single server queue are discussed. The service time and the interarrivai time densities are assumed to belong to (positive) exponential families. The queueing system is observed over a continuous time interval (0,T] whereT is determined by a suitable stopping rule. The limit distributions of the estimates are obtained in a unified setting, and without imposing the ergodicity condition on the queue length process. Generalized linear models, in particular, log-linear models are considered when several independent queues are observed. The mean service times and the mean interarrival times after appropriate transformations are assumed to satisfy a linear model involving unknown parameters of interest, and known covariates. These models enhance the scope and the usefulness of the standard queueing systems.Partially supported by the U. S. Army Research Office through the Mathematical Sciences Institute of Cornell University.     

Integral representation of a solution of the Neumann problem for the Stokes system

The Neumann problem for the Stokes system is studied on a domain in R ³ with Ljapunov bounded boundary. We construct a solution of this problem in the form of appropriate potentials and determine unknown source densities via integral equation systems on the boundary of the domain. The solution is given explicitly in the form of a series.     

Isoperimetric inequalities for infinite hyperplane systems

Let be an infinite discrete system ofk-dimensional flats inn-dimensional Euclidean space. If the totalk-dimensional volume of the flats in intersected with the ball of center 0 and radiusr, divided by the volume of that ball, tends to a limit forr→∞, then this limit is called thedensity of . We consider isoperimetric problems of the following kind. If is a hyperplane system of positive density, find sharp upper bounds for the density of the system ofk-flats (k∈{0, ...,n−2}) that are generated as intersections of hyperplanes in . Ideas from the theory of uniform distribution of sequences are employed to define a large class of hyperplane systems, calleduniform, for which all necessary densities exist, isperimetric inequalities can be proved, and systems with extremal intersection densities can be characterized.     

Direct importance estimation for covariate shift adaptation

A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likelihood estimation are no longer consistent—weighted variants according to the ratio of test and training input densities are consistent. Therefore, accurately estimating the density ratio, called the importance, is one of the key issues in covariate shift adaptation. A naive approach to this task is to first estimate training and test input densities separately and then estimate the importance by taking the ratio of the estimated densities. However, this naive approach tends to perform poorly since density estimation is a hard task particularly in high dimensional cases. In this paper, we propose a direct importance estimation method that does not involve density estimation. Our method is equipped with a natural cross validation procedure and hence tuning parameters such as the kernel width can be objectively optimized. Furthermore, we give rigorous mathematical proofs for the convergence of the proposed algorithm. Simulations illustrate the usefulness of our approach.     

Model Selection Using the Estimative and the Approximate p* Predictive Densities

Model selection procedures, based on a simple cross-validation technique and on suitable predictive densities, are taken into account. In particular, the selection criterion involving the estimative predictive density is recalled and a procedure based on the approximate p* predictive density is defined. This new model selection procedure, compared with some other well-known techniques on the basis of the squared prediction error, gives satisfactory results. Moreover, higher-order asymptotic expansions for the selection statistics based on the estimative and the approximate p* predictive densities are derived, whenever a natural exponential model is assumed. These approximations correspond to meaningful modifications of the Akaike's model selection statistic.     

Various products for Lebesgue densities

In Macheras and Strauss (Atti Sem Math Fis Univ Modena, L, pp 349–361, 2002) and Musial et al. (J Theor Probab 20:545–560, 2007) various products for primitive liftings in the factors of a product of probability spaces have been considered. In this paper we settle for the d-dimensional Lebesgue densities open problems from Macheras and Strauss (Atti Sem Math Fis Univ Modena, L, pp 349–361, 2002) and Musial et al. (J Theor Probab 20:545–560, 2007) by applying results relying on the metrical group structure of \mathbb R^d{{\mathbb R}^d}, if d ? \mathbb N{d\in{\mathbb N}}. In particular, a lifting problem from Musial et al. (Arch Math 83:467–480, 2004), Question 3.3, is decided to the negative for the Lebesgue densities. The relation of the Lebesgue density in the product space and the results of the products taken for the Lebesgue densities in the factors under order is discussed. The results can be carried over to densities and liftings dominating Lebesgue densities and to multiplicative and positive linear liftings on function spaces.