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100%: J. Keilson: Markov Chain Models - Rarity and Exponentiality (ISBN: 9783540904052) 1979, in Englisch, Taschenbuch.
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89%: Keilson, J.: Markov Chain Models-Rarity and Exponentiality (Applied Mathematical Sciences 28) (ISBN: 9780387904054) 1979, Springer, Deutschland, in Englisch, Taschenbuch.
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Markov Chain Models - Rarity and Exponentiality (1979)
EN PB NW RPISBN: 9780387904054 bzw. 0387904050, in Englisch, Springer Apr 1979, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. O.l. Time-Reversibility and Spectral Representation. Continuous time chains may be discussed in terms of discrete time chains by a uniformizing procedure ( 2.l) that simplifies and unifies the theory and enables results for discrete and continuous time to be discussed simultaneously. Thus if N(t) is any finite Markov chain in continuous time governed by transition rates vmn one may write for pet) = [Pmn(t)] - P[N(t) = n I N(O) = m] pet) = exp [-vt(I - a )] (0.1.1) v where v Max r v ' and mn m n law ~ 1 - v-I Hence N(t) where is governed r vmn Nk = NK(t) n K(t) is a Poisson process of rate v indep- by a ' and v dent of N - k Time-reversibility ( 1.3, 2.4, 2.S) is important for many reasons. A) The only broad class of tractable chains suitable for stochastic models is the time-reversible class. 204 pp. Englisch.
This item is printed on demand - Print on Demand Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. O.l. Time-Reversibility and Spectral Representation. Continuous time chains may be discussed in terms of discrete time chains by a uniformizing procedure ( 2.l) that simplifies and unifies the theory and enables results for discrete and continuous time to be discussed simultaneously. Thus if N(t) is any finite Markov chain in continuous time governed by transition rates vmn one may write for pet) = [Pmn(t)] - P[N(t) = n I N(O) = m] pet) = exp [-vt(I - a )] (0.1.1) v where v Max r v ' and mn m n law ~ 1 - v-I Hence N(t) where is governed r vmn Nk = NK(t) n K(t) is a Poisson process of rate v indep- by a ' and v dent of N - k Time-reversibility ( 1.3, 2.4, 2.S) is important for many reasons. A) The only broad class of tractable chains suitable for stochastic models is the time-reversible class. 204 pp. Englisch.
2
Markov Chain Models - Rarity and Exponentiality
EN NWISBN: 9780387904054 bzw. 0387904050, in Englisch, Springer, Deutschland, neu.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
Publisher/Verlag: Springer, Berlin | in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly.O.l. Time-Reversibility and Spectral Representation. Continuous time chains may be discussed in terms of discrete time chains by a uniformizing procedure (2.l) that simplifies and unifies the theory and enables results for discrete and continuous time to be discussed simultaneously. Thus if N(t) is any finite Markov chain in continuous time governed by transition rates vmn one may write for pet) = [Pmn(t)] - P[N(t) = n I N(O) = m] pet) = exp [-vt(I - a )] (0.1.1) v where v Max r v ' and mn m n law ~ 1 - v-I Hence N(t) where is governed r vmn Nk = NK(t) n K(t) is a Poisson process of rate v indep- by a ' and v dent of N - k Time-reversibility (1.3,2.4,2.S) is important for many reasons. A) The only broad class of tractable chains suitable for stochastic models is the time-reversible class. | 0. Introduction and Summary.- 1. Discrete Time Markov Chains; Reversibility in Time.-1.00. Introduction.-1.0. Notation, Transition Laws.-1.1. Irreducibility, Aperiodicity, Ergodicity; Stationary Chains.-1.2. Approach to Ergodicity; Spectral Structure, Perron-Romanovsky-Frobenius Theorem.-1.3. Time-Reversible Chains.- 2. Markov Chains in Continuous Time; Uniformization; Reversibility.-2.00. Introduction.-2.0. Notation, Transition Laws; A Review.-2.1. Uniformizable Chains - A Bridge Between Discrete and Continuous Time Chains.-2.2. Advantages and Prevalence of Uniformizable Chains.-2.3. Ergodicity for Continuous Time Chains.-2.4. Reversibility for Ergodic Markov Chains in Continuous Time.-2.5. Prevalence of Time-Reversibility.- 3. More on Time-Reversibility; Potential Coefficients; Process Modification.-3.00. Introduction.-3.1. The Advantages of Time-Reversibility.-3.2. The Spectral Representation.-3.3. Potentials; Spectral Representation.-3.4. More General Time-Reversible Chains.-3.5. Process Modifications Preserving Reversibility.-3.6. Replacement Processes.- 4. Potential Theory, Replacement, and Compensation.-4.00. Introduction.-4.1. The Green Potential.-4.2. The Ergodic Distribution for a Replacement Process.-4.3. The Compensation Method.-4.4. Notation for the Homogeneous Random Walk.-4.5. The Compensation Method Applied to the Homogeneous Random Walk Modified by Boundaries.-4.6. Advantages of the Compensation Method. An Illustrative Example.-4.7. Exploitation of the Structure of the Green Potential for the Homogeneous Random Walk.-4.8. Similar Situations.- 5. Passage Time Densities in Birth-Death Processes; Distribution Structure.-5.00. Introduction.-5.1. Passage Time Densities for Birth-Death Processes.-5.2. Passage Time Moments for a Birth-Death Process.-5.3. PF?, Complete Monotonicity, Log-Concavity and Log-Convexity.-5.4. Complete Monotonicity and Log-Convexity.-5.5. Complete Monotonicity in Time-Reversible Processes.-5.6. Some Useful Inequalities for the Families CM and PF?.-5.7. Log-Concavity and Strong Unimodality for Lattice Distributions.-5.8. Preservation of Log-Concavity and Log-Convexity under Tail Summation and Integration.-5.9. Relation of CM and PF? to IFR and DFR Classes in Reliability.- 6. Passage Times and Exit Times for More General Chains.-6.00. Introduction.-6.1. Passage Time Densities to a Set of States.-6.2. Mean Passage Times to a Set via the Green Potential.-6.3. Ruin Probabilities via the Green Potential.-6.4. Ergodic Flow Rates in a Chain.-6.5. Ergodic Exit Times, Ergodic Sojourn Times, and Quasi-Stationary Exit Times.-6.6. The Quasi-Stationary Exit Time. A Limit Theorem.-6.7. The Connection Between Exit.
Publisher/Verlag: Springer, Berlin | in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly.O.l. Time-Reversibility and Spectral Representation. Continuous time chains may be discussed in terms of discrete time chains by a uniformizing procedure (2.l) that simplifies and unifies the theory and enables results for discrete and continuous time to be discussed simultaneously. Thus if N(t) is any finite Markov chain in continuous time governed by transition rates vmn one may write for pet) = [Pmn(t)] - P[N(t) = n I N(O) = m] pet) = exp [-vt(I - a )] (0.1.1) v where v Max r v ' and mn m n law ~ 1 - v-I Hence N(t) where is governed r vmn Nk = NK(t) n K(t) is a Poisson process of rate v indep- by a ' and v dent of N - k Time-reversibility (1.3,2.4,2.S) is important for many reasons. A) The only broad class of tractable chains suitable for stochastic models is the time-reversible class. | 0. Introduction and Summary.- 1. Discrete Time Markov Chains; Reversibility in Time.-1.00. Introduction.-1.0. Notation, Transition Laws.-1.1. Irreducibility, Aperiodicity, Ergodicity; Stationary Chains.-1.2. Approach to Ergodicity; Spectral Structure, Perron-Romanovsky-Frobenius Theorem.-1.3. Time-Reversible Chains.- 2. Markov Chains in Continuous Time; Uniformization; Reversibility.-2.00. Introduction.-2.0. Notation, Transition Laws; A Review.-2.1. Uniformizable Chains - A Bridge Between Discrete and Continuous Time Chains.-2.2. Advantages and Prevalence of Uniformizable Chains.-2.3. Ergodicity for Continuous Time Chains.-2.4. Reversibility for Ergodic Markov Chains in Continuous Time.-2.5. Prevalence of Time-Reversibility.- 3. More on Time-Reversibility; Potential Coefficients; Process Modification.-3.00. Introduction.-3.1. The Advantages of Time-Reversibility.-3.2. The Spectral Representation.-3.3. Potentials; Spectral Representation.-3.4. More General Time-Reversible Chains.-3.5. Process Modifications Preserving Reversibility.-3.6. Replacement Processes.- 4. Potential Theory, Replacement, and Compensation.-4.00. Introduction.-4.1. The Green Potential.-4.2. The Ergodic Distribution for a Replacement Process.-4.3. The Compensation Method.-4.4. Notation for the Homogeneous Random Walk.-4.5. The Compensation Method Applied to the Homogeneous Random Walk Modified by Boundaries.-4.6. Advantages of the Compensation Method. An Illustrative Example.-4.7. Exploitation of the Structure of the Green Potential for the Homogeneous Random Walk.-4.8. Similar Situations.- 5. Passage Time Densities in Birth-Death Processes; Distribution Structure.-5.00. Introduction.-5.1. Passage Time Densities for Birth-Death Processes.-5.2. Passage Time Moments for a Birth-Death Process.-5.3. PF?, Complete Monotonicity, Log-Concavity and Log-Convexity.-5.4. Complete Monotonicity and Log-Convexity.-5.5. Complete Monotonicity in Time-Reversible Processes.-5.6. Some Useful Inequalities for the Families CM and PF?.-5.7. Log-Concavity and Strong Unimodality for Lattice Distributions.-5.8. Preservation of Log-Concavity and Log-Convexity under Tail Summation and Integration.-5.9. Relation of CM and PF? to IFR and DFR Classes in Reliability.- 6. Passage Times and Exit Times for More General Chains.-6.00. Introduction.-6.1. Passage Time Densities to a Set of States.-6.2. Mean Passage Times to a Set via the Green Potential.-6.3. Ruin Probabilities via the Green Potential.-6.4. Ergodic Flow Rates in a Chain.-6.5. Ergodic Exit Times, Ergodic Sojourn Times, and Quasi-Stationary Exit Times.-6.6. The Quasi-Stationary Exit Time. A Limit Theorem.-6.7. The Connection Between Exit.
3
Markov Chain Models - Rarity and Exponentiality (1979)
EN PB NWISBN: 9780387904054 bzw. 0387904050, in Englisch, Springer Apr 1979, Taschenbuch, neu.
Von Händler/Antiquariat, Rhein-Team Lörrach Ivano Narducci e.K. [57451429], Lörrach, Germany.
Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. 204 pp. Englisch.
Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. 204 pp. Englisch.
4
Markov Chain Models - Rarity and Exponentiality (1979)
EN PB NWISBN: 9780387904054 bzw. 0387904050, in Englisch, Springer Apr 1979, Taschenbuch, neu.
Von Händler/Antiquariat, Agrios-Buch [57449362], Bergisch Gladbach, Germany.
Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. 204 pp. Englisch.
Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. 204 pp. Englisch.
5
Markov Chain Models - Rarity and Exponentiality (1979)
EN PB NWISBN: 9780387904054 bzw. 0387904050, in Englisch, Springer Apr 1979, Taschenbuch, neu.
Von Händler/Antiquariat, Rheinberg-Buch [53870650], Bergisch Gladbach, Germany.
Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. 204 pp. Englisch.
Neuware - in failure time distributions for systems modeled by finite chains. This introductory chapter attempts to provide an over view of the material and ideas covered. The presentation is loose and fragmentary, and should be read lightly initially. Subsequent perusal from time to time may help tie the mat erial together and provide a unity less readily obtainable otherwise. The detailed presentation begins in Chapter 1, and some readers may prefer to begin there directly. 204 pp. Englisch.
6
Markov Chain Models - Rarity and Exponentiality (1979)
DE PBISBN: 9783540904052 bzw. 3540904050, in Deutsch, Springer-Verlag Berlin and Heidelberg GmbH & Co. K, Taschenbuch.
Von Händler/Antiquariat, medimops [55410863], Berlin, Germany.
Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
7
Markov Chain Models - Rarity and Exponentiality (1979)
DE PB USISBN: 9783540904052 bzw. 3540904050, in Deutsch, Springer-Verlag Berlin and Heide, Taschenbuch, gebraucht.
Von Händler/Antiquariat, Books From California [939515], Simi Valley, CA, U.S.A.
Ex-library copy with usual markings. Text is clean.
Ex-library copy with usual markings. Text is clean.
8
Markov Chain Models - Rarity and Exponentielity. (= Applied Mathematical Sciences, 28). (1979)
DE PB USISBN: 9783540904052 bzw. 3540904050, in Deutsch, New York etc.: Springer-Verlag, Taschenbuch, gebraucht.
Lieferung aus: Deutschland, Versandkosten nach: Deutschland.
Von Händler/Antiquariat, Antiquariat für Fachliteratur Matthias Gleim, [3586214].
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Von Händler/Antiquariat, Antiquariat für Fachliteratur Matthias Gleim, [3586214].
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Markov Chain Models - Rarity and Exponentiality (1979)
DE PB USISBN: 9783540904052 bzw. 3540904050, in Deutsch, 184 Seiten, Springer-Verlag GmbH, Taschenbuch, gebraucht.
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Markov Chain Models - Rarity and Exponentiality (1979)
EN PB USISBN: 9783540904052 bzw. 3540904050, in Englisch, 184 Seiten, Springer-Verlag GmbH, Taschenbuch, gebraucht.
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