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	<title>BookPasta.net &#187; Probability</title>
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	<link>http://bookpasta.net</link>
	<description>and eBookz for all</description>
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		<title>Rare Event Simulation using Monte Carlo Methods</title>
		<link>http://bookpasta.net/blog/2009/11/19/rare-event-simulation-using-monte-carlo-methods/</link>
		<comments>http://bookpasta.net/blog/2009/11/19/rare-event-simulation-using-monte-carlo-methods/#comments</comments>
		<pubDate>Fri, 20 Nov 2009 03:08:21 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[Probability]]></category>
		<category><![CDATA[montecarlo]]></category>
		<category><![CDATA[rare]]></category>
		<category><![CDATA[simulation]]></category>

		<guid isPermaLink="false">http://bookpasta.net/?p=352</guid>
		<description><![CDATA[In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.]]></description>
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		<title>Dealing with Uncertainties</title>
		<link>http://bookpasta.net/blog/2009/11/17/dealing-with-uncertainties/</link>
		<comments>http://bookpasta.net/blog/2009/11/17/dealing-with-uncertainties/#comments</comments>
		<pubDate>Tue, 17 Nov 2009 21:18:28 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[Probability]]></category>
		<category><![CDATA[correlation]]></category>
		<category><![CDATA[measurement]]></category>
		<category><![CDATA[uncertainty]]></category>

		<guid isPermaLink="false">http://bookpasta.net/?p=327</guid>
		<description><![CDATA[Dealing with Uncertainties proposes and explains a new approach for the analysis of uncertainties. Firstly, it is shown that uncertainties are the consequence of modern science rather than of measurements. Secondly, it stresses the importance of the deductive approach to uncertainties. This perspective has the potential of dealing with the uncertainty of a single data point and of data of a set having differing weights. Both cases cannot be dealt with the inductive approach, which is usually taken. This innovative monograph also fully covers both uncorrelated and correlated uncertainties. The weakness of using statistical weights in regression analysis is discussed. Abundant examples are given for correlation in and between data sets and for the feedback of uncertainties on experiment design.]]></description>
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		<title>Bayesian Theory</title>
		<link>http://bookpasta.net/blog/2009/11/15/bayesian-theory/</link>
		<comments>http://bookpasta.net/blog/2009/11/15/bayesian-theory/#comments</comments>
		<pubDate>Mon, 16 Nov 2009 04:33:43 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[Probability]]></category>
		<category><![CDATA[bayesian]]></category>
		<category><![CDATA[multivariate]]></category>
		<category><![CDATA[random]]></category>

		<guid isPermaLink="false">http://bookpasta.net/?p=299</guid>
		<description><![CDATA[This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion of the problem of specification of so-called ‘prior ignorance. The work is written from the authorss committed Bayesian perspective, but an overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critical re-examination of controversial issues. The level of mathematics used is such that most material is accessible to readers with knowledge of advanced calculus. In particular, no knowledge of abstract measure theory is assumed, and the emphasis throughout is on statistical concepts rather than rigorous mathematics. The book will be an ideal source for all students and researchers in statistics, mathematics, decision analysis, economic and business studies, and all branches of science and engineering, who wish to further their understanding of Bayesian statistics]]></description>
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		<title>Probability Random Processes And Ergodic Properties 2nd Edition</title>
		<link>http://bookpasta.net/blog/2009/11/04/springer-probability-random-processes-and-ergodic-properties-2nd-edition/</link>
		<comments>http://bookpasta.net/blog/2009/11/04/springer-probability-random-processes-and-ergodic-properties-2nd-edition/#comments</comments>
		<pubDate>Thu, 05 Nov 2009 03:02:07 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[Probability]]></category>
		<category><![CDATA[communications]]></category>
		<category><![CDATA[ergodic]]></category>
		<category><![CDATA[networks]]></category>
		<category><![CDATA[probability]]></category>
		<category><![CDATA[signal]]></category>
		<category><![CDATA[stochastic]]></category>

		<guid isPermaLink="false">http://bookpasta.net/?p=16</guid>
		<description><![CDATA[Probability, Random Processes, and Ergodic Properties is for mathematically inclined information/communication theorists and people working in signal processing. It will also interest those working with random or stochastic processes, including mathematicians, statisticians, and economists. Highlights Second edition of classic text Complete tour of book and guidelines for use given in Introduction, so readers can see at a glance the topics of interest Structures mathematics for an engineering audience, with emphasis on engineering applications. New in the Second Edition Much of the material has been rearranged and revised for pedagogical reasons. The original first chapter has been split in order to allow a more thorough treatment of basic probability before tackling random processes and dynamical systems. The final chapter has been broken into two pieces to provide separate emphasis on process metrics and the ergodic decomposition of affine functionals. Completion of event spaces and probability measures is treated in more detail. More specific examples of random processes have been introduced. Many classic inequalities are now incorporated into the text, along with proofs; and many citations have been added. From the Author’s Preface&#8230; This book has a long history. It began over two decades ago as the first half of a book [...]]]></description>
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