scholarly journals A lemma on stochastic majorization and properties of the Student distribution

10.4213/tvp16 ◽  
2007 ◽  
Vol 52 (1) ◽  
pp. 199-203
Author(s):  
Абрам Меерович Каган ◽  
Abram Meerovich Kagan ◽  
Aleksandr Viktorovich Nagaev ◽  
Aleksandr Viktorovich Nagaev
Keyword(s):  
Student Distribution ◽  
Stochastic Majorization

A Lemma on Stochastic Majorization and Properties of the Student Distribution

2008 ◽  
Vol 52 (1) ◽  
pp. 160-164
Author(s):  
A. Kagan ◽  
A. V. Nagaev
Keyword(s):  
Student Distribution ◽  
Stochastic Majorization

An extremal property of the student distribution

1989 ◽  
Vol 44 (4) ◽  
pp. 433-440 ◽  
Author(s):  
N. K. Bakirov
Keyword(s):  
Extremal Property ◽  
Student Distribution

Modeling of Magnetic Hysteresis Using Student Distribution

2020 ◽  
Vol 33 (12) ◽  
pp. 3865-3869
Author(s):  
Mourad Dafri ◽  
Abdelaziz Lajimi ◽  
Sofiane Mendaci ◽  
Abdesselam Babouri
Keyword(s):  
Magnetic Hysteresis ◽  
Student Distribution

Statistical Methodologies for Reliability Assessment of Gas Turbine Measurements

2003 ◽  
Author(s):  
M. Pinelli ◽  
M. Venturini ◽  
M. Burgio
Keyword(s):  
Data Processing ◽  
Mathematical Models ◽  
Gas Turbine ◽  
Measurement Errors ◽  
Field Data ◽  
Reliability Assessment ◽  
Field Measurements ◽  
Measurement Reliability ◽  
Student Distribution ◽  
Analysis Models

All measurements, although taken as accurately as possible, are subjected to uncertainty. So the analysis of errors and uncertainty is crucial in all applications since such errors need to be estimated and, when possible, reduced. In particular, when gas turbine mathematical models based on the processing of field measurements (such as the Gas Path Analysis models) are used, the evaluation of measurement reliability is a key point. In fact, it has been demonstrated that these kinds of techniques are sensitive to measurement errors: thus, tools for field data processing to evaluate the presence of the so-called outliers are advisable. In this paper, some statistical methodologies for the assessment of the reliability of the measurements taken on a gas turbine are presented. The methodologies, taken from literature and used for historical measurements, are discussed. Moreover, a new methodology, based on a modified t-Student distribution, is proposed.

A new ordering for stochastic majorization: theory and applications

1992 ◽  
Vol 24 (03) ◽  
pp. 604-634 ◽  
Author(s):  
Cheng-Shang Chang
Keyword(s):  
Sample Path ◽  
Stochastic Ordering ◽  
Partial Ordering ◽  
Scheduling Problems ◽  
Unified Approach ◽  
Finite Buffers ◽  
Routing And Scheduling ◽  
Partial Orderings ◽  
Stochastic Load ◽  
Stochastic Majorization

In this paper, we develop a unified approach for stochastic load balancing on various multiserver systems. We expand the four partial orderings defined in Marshall and Olkin, by defining a new ordering based on the set of functions that are symmetric, L-subadditive and convex in each variable. This new partial ordering is shown to be equivalent to the previous four orderings for comparing deterministic vectors but differs for random vectors. Sample-path criteria and a probability enumeration method for the new stochastic ordering are established and the ordering is applied to various fork-join queues, routing and scheduling problems. Our results generalize previous work and can be extended to multivariate stochastic majorization which includes tandem queues and queues with finite buffers.

Right gut-majorization on M_{n,m}

2016 ◽  
Vol 31 ◽  
pp. 13-26
Author(s):  
Asma Manesh
Keyword(s):  
Stochastic Matrix ◽  
Linear Preservers ◽  
Stochastic Majorization

Let M_{n,m} be the set of all n-by-m matrices with entries from R, and suppose that R^n is the set of all 1-by-n real row vectors. A matrix R is called generalized row stochastic (g-row stochastic) if the sum of entries on every row of R is 1. For X, Y ∈ M_{n,m}, it is said that X is rgut-majorized by Y (denoted by X ≺_{rgut} Y ) if there exists an m-by-m upper triangular g-row stochastic matrix R such that X = Y R. In this paper, the concept right upper triangular generalized row stochastic majorization, or rgut- majorization, is investigated and then the linear preservers and strong linear preservers of this concept are characterized on R^n and M_{n,m}.

Stochastic comparisons for fork-join queues with exponential processing times

1997 ◽  
Vol 34 (2) ◽  
pp. 487-497 ◽  
Author(s):  
Esther Frostig ◽  
Tapani Lehtonen
Keyword(s):  
Random Variables ◽  
Single Server ◽  
Departure Process ◽  
Stochastic Comparisons ◽  
Processing Times ◽  
Service Rates ◽  
Service Times ◽  
Stochastic Majorization

Consider a fork-join queue, where each job upon arrival splits into k tasks and each joins a separate queue that is attended by a single server. Service times are independent, exponentially distributed random variables. Server i works at rate , where μ is constant. We prove that the departure process becomes stochastically faster as the service rates become more homogeneous in the sense of stochastic majorization. Consequently, when all k servers work with equal rates the departure process is stochastically maximized.

New Bounds for Timed Event Graphs Inspired by Stochastic Majorization Results

2004 ◽  
Vol 14 (4) ◽  
pp. 355-380
Author(s):  
L. Truffet
Keyword(s):  
Stochastic Majorization ◽  
Timed Event Graphs
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