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New Book
Statistical Data Analysis, Modeling and Study of Probability
Regularities. Computer Approach:
monograph
B.Yu. Lemeshko, S.B. Lemeshko, S.N. Postovalov, E.V. Chimitova.
Novosibirsk : NSTU Publisher, 2011. – 888 pp. (“NSTU Monographs”
series).
ISBN 978-5-7782-1590-0
Issues relating to applying statistical analysis methods are addressed
in the monograph. Problems of estimating parameters for point, censored,
grouped and interval samples are discussed. Differences between estimate
properties under limited amounts of samples and asymptotic properties of
the same estimates are studied. The use of the χ2 goodness-of-fit tests
and the effect of factors on the test power (i.e. the number of
intervals and ways of grouping) are considered. The use of nonparametric
goodness-of-fit tests (Kolmogorov’s, Kramer–Mises–Smirnov’s and
Anderson–Darling’s) when testing complex hypotheses is discussed. A lot
of models of distributed statistics of these tests when checking various
complex hypotheses are provided. The results of a comparative analysis
of the power of parametric and nonparametric goodness-of-fit tests are
given. The results of study of properties of various tests of hypotheses
of empirical distribution abnormality are given, Advantages and
disadvantages of some tests are emphasized and the results of a
comparative analysis of tests power are provided. Properties and power
of nonparametric tests for homogeneity are studied. The stability of
classical tests for homogeneity of means against the departure from the
normal law is demonstrated and a comparative analysis of parametric and
nonparametric test power is made. A comparative analysis of classical
test power in checking hypotheses of variances homogeneity is made as
well as an analysis of nonparametric criteria of testing hypotheses of
variance characteristics equality. A possibility of using classical
tests for homogeneity of variances with distribution abnormality laws is
shown. Tests for the rejection of abnormal measurements and tests of the
presence of a trend are studied and analyzed. A lot of tables that
present the results of the study and help to use correctly the proposed
methods of statistical analysis are given in the appendices. The book is
intended for undergraduate, graduate and postgraduate students,
university teachers, researchers and specialists in various fields (e.g.
engineers, economists, physicians, etc.) who need to analyze the results
of their experimental research.
Network Reliability and Resilience
(SpringerBriefs in Electrical and Computer Engineering)
Ilya Gertsbakh,
Yoseph Shpungin
Paperback: 74 pages
Publisher: Springer; 1st Edition. edition (September 3, 2011)
Language: English
ISBN-10: 3642223737
ISBN-13: 978-3642223730
Product Dimensions: 9.1 x 5.9 x 0.6 inches
This book is devoted to the probabilistic description of the behavior of
a network in the process of random removal of its components (links,
nodes) appearing as a result of technical failures, natural disasters or
intentional attacks. It is focused on a practical approach to network
reliability and resilience evaluation, based on applications of Monte
Carlo methodology to numerical approximation of network combinatorial
invariants, including so-called multidimensional destruction spectra.
This allows to develop a probabilistic follow-up analysis of the network
in the process of its gradual destruction, to identify most important
network components and to develop efficient heuristic algorithms for
network optimal design. Our methodology works with satisfactory accuracy
and efficiency for most applications of reliability theory to real –life
problems in networks.
 Applied
Nonparametric Statistics in Reliability
Series: Springer
Series in Reliability Engineering
Gámiz, M.L., Kulasekera, K.B., Limnios, N., Lindqvist, B.H.
1st Edition., 2011, XIII, 230 p. 41 illus.
Hardcover, ISBN 978-0-85729-117-2
Usually dispatched within 3 to 5 business days
99,95 €
ABOUT THIS BOOK
Nonparametric statistics has probably become the leading methodology for
researchers performing data analysis.
It is nevertheless true that, whereas these methods have already proved
highly effective in other applied areas of knowledge such as
biostatistics or social sciences, nonparametric analyses in reliability
currently form an interesting area of study that has not yet been fully
explored. Applied Nonparametric Statistics in Reliability is focused on
the use of modern statistical methods for the estimation of
dependability measures of reliability systems that operate under
different conditions. The scope of the book includes: smooth estimation
of the reliability function and hazard rate of non-repairable systems;
study of stochastic processes for modelling the time evolution of
systems when imperfect repairs are performed; nonparametric analysis of
discrete and continuous time semi-Markov processes; isotonic regression
analysis of the structure function of a reliability system, and lifetime
regression analysis. Besides the explanation of the mathematical
background, several numerical computations or simulations are presented
as illustrative examples. The corresponding computer-based methods have
been implemented using R and MATLAB®. A concrete modelling scheme is
chosen for each practical situation and, in consequence, a nonparametric
inference procedure is conducted. Applied Nonparametric Statistics in
Reliability will serve the practical needs of scientists (statisticians
and engineers) working on applied reliability subjects.
Mathematical and Statistical Models and Methods in Reliability
Applications to Medicine, Finance, and Quality Control
Rykov, V.V.; Balakrishnan, N.; Nikulin, M.S. (Eds.)
1st Edition., 2010, XXVI, 457 p. 74 illus.
A product of Birkhäuser Boston
Hardcover, ISBN
978-0-8176-4970-8
An outgrowth of the sixth conference on “Mathematical Methods in
Reliability: Theory, Methods, and Applications,” this book is a
selection of invited chapters, all of which deal with various aspects of
mathematical and statistical models and methods in reliability.
Written by recognized experts in the field of reliability, the
contributions cover a wide range of models, methods, and applications,
reflecting recent developments in areas such as survival analysis,
aging, lifetime data analysis, artificial intelligence, medicine,
carcinogenesis studies, nuclear power, financial modeling, aircraft
engineering, quality control, and transportation.
The volume is thematically organized into four major sections:
*
Reliability Models, Methods, and Optimization;
*
Statistical Methods in Reliability;
*
Applications;
*
Computer Tools for Reliability.
Mathematical and Statistical Models and Methods in Reliability is an
excellent reference text for researchers and practitioners in applied
probability and statistics, industrial statistics, engineering,
medicine, finance, transportation, the oil and gas industry, and
artificial intelligence.
Nonparametric Tests for Censored Data
Vilijandas Bagdonavicus, Julius Kruopis, Mikhail Nikulin
ISBN: 978-1-84821-289-3
Hardcover
January 2011, Wiley-ISTE
US $95.00
This book concerns testing hypotheses in non-parametric models.
Generalizations of many non-parametric tests to the case of censored and
truncated data are considered. Most of the test results are proved and
real applications are illustrated using examples. Theories and exercises
are provided. The incorrect use of many tests applying most statistical
software is highlighted and discussed.
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G.P. Klimov
Invariant Statistical
Desisions
The book based on course
of lectures at Universities
of Russia, United States,
Poland, Germany and Belgium.
Published by Moscow State
University (Russia). |
G.P. Klimov
Queuing Theory
The book based on course
of lectures at Universities
of Russia, United States,
Poland, Germany and Belgium.
Published by Moscow
State University (Russia).
|
G.P. Klimov
Probability Theory
and Mathematical Statistics
The book based on course
of lectures at Universities
of Russia, United States, Poland,
Germany and Belgium.
Published by Moscow State
University (Russia). |
Decomposable Semi-Regenerative Processes. And Their Applications
(Paperback)
Publisher: Lap Lambert Academic Publishin
A very known notion of regeneration means that the "future" of a
stochastic process became independent from its "past" in some random
times, which is usually times of some state (regeneration state)
destination. Presence of regeneration times allows to represent
appropriate process as independent functional elements, regeneration
cycles, investigate its characteristics in terms of them at separate
regeneration cycles and proof some asymptotic theorem about this
type of processes. If there are several such regeneration states
this notion is generalized up to notion of semi- regeneration. In
this case the process could be represented as a Markov chain of its
cycles. Next step of generalization consists in discovering of some
embedded regeneration times that allows to construct some
hierarchical structure for the processes, possessing this property.
This processes are named as decomposable semi-regenerative
processes. The methods of these processes applied then for the
investigation of several models: M/GI/1 queuing system, M_r/GI_r/1
priority queuing system, GI/GI/1 queuing system, polling system and
reliability of complex hierarchical system.
Table of Contents
Mathematical Statistics and Experiment Design
Gubkin Russian State University of Oil and Gas
Applied Mathematics for Engineers
by
V.V. RYKOV,
V.Yu.Itkon
Moscow, 2009
This issue is a text book that has been done during several years
for students in Applied Mathematics of Gubkin Russian State
University of Oil and Gas. Some specific contains in e3xamples and
materials for students work that are oriented to application in oil
and gas industry.
Table of contents available or Russian
Stochastic Processes. Diffusion Processes and Processes with Independent
Increments
Lections to the course on Applied Stochastic Models
Peoples’ Friendship University of Russia
Probability Theory and Mathematical Statistics Department
by
V.V. RYKOV
Moscow, 2010
This issue is the second part of a previous one. This is a course of
lections that during several years has been done for students of
Applied Mathematics of Gubkin Russian State University of Oil & Gas
and for students of Probability Theory and Mathematical Statistics
of Peoples’ Friendship University of Russia.
The course is based on the traditional material for stochastic
processes and being oriented to application its peculiarities are
commentaries instead of strong proofs of some theorems.
Table of contents available or Russian
This book includes notes of lectures given over the years to
students majoring in applied mathematics and computer simulation of
the Russian State University of Oil and Gas, and students majoring
in Probability and Mathematical Statistics of the Russian Peoples'
Friendship University.
The material is based on traditional courses, the theory of random
processes. Some features of this course designed for students
majoring in Applied Mathematics and Computer Science, is the
replacement of complete proofs of some fundamental theorems of their
comments, allowing to understand the peculiarities of the evidence
around complex and tedious calculations show the presence of "thin
places", but did not investigate them thoroughly.
The basic unit of the course is a paragraph so numbered formulas,
figures, tables, theorems, etc. own within each section. When
referring to formulas from other sections use double numbering. At
the end of each section are questions for self-assessment exercises,
tasks and brief bibliographical comments.
For students majoring in Applied Mathematics and Computer Science,
Computer Science. "
The author is particularly grateful to V.A. Kokotushkin who prepared
part of the tasks, as well as D.V. Kozyrev be of great help in the
preparation and presentation of a text.
Table of contents available or Russian
 Operational
Risk Management: a practical approach to intelligent data analysis
ISBN
9780470517666
Publisher: John Wiley and Sons,
Chichester
Editors:
Ron S. Kenett
and Yossi Raanan
Introduction to the book
Operational Risk Management is becoming a key competency for
organisations in all industries. Financial institutions, regulated
by the Basel II accord, need to address it systematically since
their level of implementation affects their capital requirements,
one of their major operational expenses. Health organisations have
been tackling this challenge for many years. The Institute of
Medicine reported in 2000 that 44,000 - 98,000 patients die each
year in the US as a result of medication errors, surgical errors and
missed diagnoses, at an estimated cost to the US economy of $17-$29
billion. Operational risks affect large organisations as well as
Small and Medium-sized Enterprises (SMEs) in virtually all
industries, from the oil and gas industry, to hospitals, from
education to public services.
This multi-author book is about
tracking and managing operational risks using state-of-the-art
technology that combines the analysis of qualitative, semantic,
unstructured data with quantitative data. The examples used are
mostly from information technology but the approach is general. As
such, the book provides knowledge and methods that can have a
substantial impact on the economy and quality of life.
The book has four main parts. Part I is
an introduction to Operational Risk Management, Part II deals with
data for Operational Risk Management and its handling, Part III
covers operational risks analytics and Part IV concludes the book
with several applications and a discussion on how Operational Risk
Management integrates with other disciplines. The fourteen chapters
and the book layout are listed below with short descriptions.
read more in
December
issue of electronic journal “Reliability: Theory & Applications”
by Isaac
Elishakoff (Florida
Atlantic University, USA) &
Makoto Ohsaki (Kyoto
University, Japan)
Table of Contents (72k)
Preface (131k)
Chapter 1: Introduction (235k)
The volume presents a collaboration between internationally
recognized experts on anti-optimization and structural optimization,
and summarizes various novel ideas, methodologies and results
studied over 20 years. The book vividly demonstrates how the concept
of uncertainty should be incorporated in a rigorous manner during
the process of designing real-world structures. The necessity of
anti-optimization approach is first demonstrated, then the
anti-optimization techniques are applied to static, dynamic and
buckling problems, thus covering the broadest possible set of
applications. Finally, anti-optimization is fully utilized by a
combination of structural optimization to produce the optimal design
considering the worst-case scenario. This is currently the only book
that covers the combination of optimization and anti-optimization.
It shows how various optimization techniques are used in the novel
anti-optimization technique, and how the structural optimization can
be exponentially enhanced by incorporating the concept of worst-case
scenario, thereby increasing the safety of the structures designed
in various fields of engineering.
-
Optimization or Making the Best in the Presence of
Certainty/Uncertainty
-
General Formulation of Anti-Optimization
-
Anti-Optimization in Static Problems
-
Anti-Optimization in Buckling
-
Anti-Optimization in Vibration
-
Anti-Optimization via FEM-Based Interval Analysis
-
Anti-Optimization and Probabilistic Design
-
Hybrid Optimization with Anti-Optimization under Uncertainty or
Making the Best Out of the Worst
Readership: Graduate students, professionals and academics in the
field of mechanical engineering.
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