1 edition of **Stochastic ordering in residual mixing distributions** found in the catalog.

Stochastic ordering in residual mixing distributions

David Russell Campbell

- 207 Want to read
- 18 Currently reading

Published
**1974**
by Naval Postgraduate School in Monterey, Calif
.

Written in English

- Stochastic processes,
- Distribution (Probability theory),
- Reliability (Engineering)

**Edition Notes**

Statement | by David R. Campbell |

Contributions | Naval Postgraduate School (U.S.) |

The Physical Object | |
---|---|

Pagination | 18 p. ; |

Number of Pages | 18 |

ID Numbers | |

Open Library | OL25506579M |

OCLC/WorldCa | 428448541 |

Stochastic Process Book Recommendations? I'm looking for a recommendation for a book on stochastic processes for an independent study that I'm planning on taking in the next semester. Something that doesn't go into the full blown derivations from a measure theory point of view, but still gives a thorough treatment of the subject. Title: Stochastic ordering of classical discrete distributions Authors: Achim Klenke, Lutz Mattner (Submitted on 7 Mar (v1), last revised 7 Mar (this version, v2)).

It is now more than a year later, and the book has been written. The ﬁrst three chapters develop probability theory and introduce the axioms of probability, random variables, and joint distributions. The following two chapters are shorter and of an “introduction to” nature: Chapter 4 on limit theorems and Ch apter 5 on simulation. The series founded in and formerly entitled Applications of Mathematics published high-level research monographs that make a significant contribution to some field of application or methodology from stochastic analysis, while maintaining rigorous mathematical standards, and also displaying the expository quality to make them useful and accessible to doctoral students.

S. Resnick, `Adventures in Stochastic Processes'. The course will closely follow this book; it is available at the campus bookstore. Also, Amazon quotes currently (4/) a prize reduction by 14% Further suggested reading Ross, `Introduction to Probability Models' A. Papoulis, `Probability, Random Variables, and Stochastic Processes'. In Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, readers are able to grasp the concepts of probability and stochastic processes, and apply these in professional engineering practice. The 3rd edition also includes quiz solutions within the appendix of the text. The resource presents concepts clearly as a .

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In this paper, we consider stochastic comparisons of mixtures (F∗ and G∗) of residual life distributions (Fθ and Gθ, θ>0) arising out of different baseline distributions (F and G) and.

In this paper, following, we consider stochastic comparisons of mixture of residual lifetime distributions arising out of different baseline distributions and/or different mixing distributions.

Suppose that the lifetime of a fresh item and its survival function (s.f.) are denoted by X and F ̄ (x), respectively, with distributional support Cited by: 1.

In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a family of random ically, the random variables were associated with or indexed by a set of numbers, usually viewed as points in time, giving the interpretation of a stochastic process representing numerical values of some system randomly changing over.

Stochastic Ordering of Exponential Family Distributions and Their Mixtures Article in Journal of Applied Probability 46(1) September with 50 Reads How we measure 'reads'. We show an interesting identity for Ef(Y) − Ef(X), where X, Yare normally distributed random vectors and f is a function fulfilling some weak regularity condition.

This identity will be used for a unified derivation of sufficient conditions for stochastic ordering results of multivariate normal distributions, some well known ones as well as some new by: Note that likelihood ratio ordering implies hazard rate ordering which in turn implies stochastic ordering.

Let F-1 and G-1 be the right continuous inverses (quantile functions) of F and G, respectively. We say that X is less dispersed than Y (denoted by X ⩽ disp Y) if F-1 (β)-F-1 (α) ⩽ G-1 (β)-G-1 (α), for all 0 ⩽ α ⩽ β ⩽ by: A new one parameter continuous distribution named “Aradhana distribution” for modeling lifetime data from biomedical science and engineering has been proposed.

Its mathematical and statistical properties including its shape, moments, hazard rate function, mean residual life function, stochastic ordering, mean deviations, order statistics, Bonferroni and Lorenz curves, Renyi. Books shelved as stochastic-processes: Introduction to Stochastic Processes by Gregory F.

Lawler, Adventures in Stochastic Processes by Sidney I. Resnick. In Chapter 1 a selection of one dimensional orderings is presented together with applications in the theory of queues, some parts of this selection are based on the recent literature (not older than five years).

In Chapter 2 the material is centered around the strong stochastic ordering in many dimen sional spaces and functional spaces. Extensively class-tested to ensure an accessible presentation, Probability, Statistics, and Stochastic Processes, Second Edition is an excellent book for courses on probability and statistics at the upper-undergraduate level.

The book is also an ideal resource for scientists and engineers in the fields of statistics, mathematics, industrial Cited by: We review some of the recent developments in the area of stochastic comparisons of order statistics and sample spacings.

We consider the cases when the parent observations are identically as well as nonidentically distributed. But most of the time we will be assuming that the observations are independent.

The case of independent exponentials with unequal scale Cited by: The $\alpha$-mixing implies mixing in the statistical (ergodic-theoretical) sense, but not the other way round.

It is nicely explained in the Samorodnitsky's book "Stochastic processes and long range dependence". For the mathematicians Advanced: Probability with Martingales, by David Williams (Good mathematical introduction to measure theoretic probability and discerete time martingales) Expert: Stochastic Integration and Differential Equations by Phil.

Probability - Random Variables and Stochastic Processes Probability, Random Variables And Stochastic Processes was designed for students who are pursuing senior or graduate level courses, in probability. Those in the disciplines of mathematics phy. Presenting probability in a natural way, this book uses interesting, carefully selected instructive examples that explain the theory, definitions, theorems, and methodology.

Fundamentals of Probability has been adopted by the American Actuarial Society as one of its main references for the mathematical foundations of actuarial by: The ordering ≤ st is called usual stochastic ordering or ﬁrst order stochastic dominance (FSD).

In a ﬁnancial setting it means that any rational decision maker, having a utility function in the sense of von Neumann-Morgenstern, prefers the return Y to the return X. In the following theorem we collect some basic results for the order.

Stochastic Process (Again, for a more complete treatment, see or the like.) Definition: A stochastic process is defined as a sequence of random variables. A stochastic process may also be called a random process, noise process, or simply signal (when the context is understood to exclude deterministic components).

$\begingroup$ @ Amr: Maybe the book by Oksendal could fit your needs, for more technical books see Karatzas and Shreeve (Brownian motion and stochastic calculus), Protter (stochastic integration and differential equation), Jacod Shyraiev (limit theorem for stochastic processes, Revuz and Yor (Continuous martingale and Brownian motion).

There are also intersting blogs. to be called Stochastic Calculus. If that comes as a disappointment to the reader, I suggest they consider C. Gardiner’s book: Handbook of stochastic methods (3rd Ed.), C. Gardiner (Springer, ), as a friendly introduction to It^o’s calculus.

A list of references useful for further study appear at the beginning. Applications of Stochastic Orders in Reliability and Mixture of Exponential family Jarrahi Feriz, J.1;2, Mohtashami Borzadaran, G. R.2 and Rezaei Roknabadi, A. H.2 1 Department of Science, Islamic Azad University, Birjand Branch, Birjand, Iran.

2 Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran. Abstract. In this paper, we have recalled some of the. Stochastic Ordering For probability measures P and Qon the real numbers, the stochastic ordering is the partial ordering P st Q P([x;1)) Q([x;1)) for all x2R: This condition is equivalent to the existence of two real-valued random variables Xand Y with distributions Pand Q, respectively, and such that X Y almost surely.

In fact, let F P and FCited by: An introduction to stochastic processes through the use of R. Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social use of simulation, by means of the popular statistical software R, makes theoretical results .0–9.

; 2SLS (two-stage least squares) – redirects to instrumental variable; 3SLS – see three-stage least squares; 68–95– rule; year flood.