This article proposes a stochastic version of the matching pursuit algorithm for Bayesian variable selection in linear regression. In the Bayesian formulation, the prior distribution of each regression coefficient is assumed to be a mixture of a point mass at 0 and a normal distribution with zero mean and a large variance. The proposed stochastic matching pursuit algorithm is designed for sampl...

The articles [22], [5], [3], [2], [4], [6], [21], [16], [14], [15], [1], [17], [19], [20], [7], [8], [9], [12], [11], [10], and [13] provide the terminology and notation for this paper. For simplicity we adopt the following rules: x is arbitrary, R is an associative ring, V is a left module over R, v, v1, v2 are vectors of V , A, B are subsets of V , and l is a linear combination of A. We now d...

A recent development in data-driven modelling addresses the problem of identifying dynamic models of interconnected systems, represented as linear dynamic networks. For these networks the notion network identifiability has been introduced recently, which reflects the property that different network models can be distinguished from each other. Network identifiability is extended to cover the uni...

for two algebras $a$ and $b$, a linear map $t:a longrightarrow b$ is called separating, if $xcdot y=0$ implies $txcdot ty=0$ for all $x,yin a$. the general form and the automatic continuity of separating maps between various banach algebras have been studied extensively. in this paper, we first extend the notion of separating map for module case and then we give a description of a linear separa...

This work introduces new relative perturbation bounds for the LDU factorization of (row) diagonally dominant matrices under structure-preserving componentwise perturbations. These bounds establish that if (row) diagonally dominant matrices are parameterized via their diagonally dominant parts and off-diagonal entries, then tiny relative componentwise perturbations of these parameters produce ti...

Questions pertaining to the admissibility of fixed sample size tests of hypotheses, when sequential tests are available, are considered. For the normal case with unknown mean, suppose the risk function is a linear combination of probability of error and expected sample size. Then any fixed sample size test, with sample size n⩾ 2, is inadmissible. On the other hand, suppose the risk function con...

A real square matrix is said to be a P-matrix if all its principal minors are positive. It is well known that this property is equivalent to: the nonsign-reversal property based on the componentwise product of vectors, the order P-property based on the minimum and maximum of vectors, uniqueness property in the standard linear complementarity problem, (Lipschitzian) homeomorphism property of the...

In the present paper, we study several qualitative properties of a class of nonlinear switched systems under certain switching laws. First, we show that if all the subsystems are linear time-invariant and the system matrices are commutative componentwise and stable, then the entire switched system is globally exponentially stable under arbitrary switching laws. Next, we study the above linear s...

This paper presents an improved version of a componentwise bounding algorithm for the state probability vector of nearly completely decomposable Markov chains, and on an application it provides the first numerical results with the type of algorithm discussed. The given two-level algorithm uses aggregation and stochastic comparison with the strong stochastic (st) order. In order to improve accur...

The idea of Componentwise Newton Operator has been presented in [9]. It seems up to now not much attention has been paid to this concept. In this paper we present properties of the Componentwise Newton Operator and show how they can be used in numerical algorithms. It seems they are especially important when transforming the problem by some symbolic methods, based on the computation of Groebner...