Markov Set-Chains

In this study extending classical Markov chain theory to handle fluctuating transition matrices, the author develops a theory of Markov set-chains and provides numerous examples showing how that theory can be applied. Chapters are concluded with a discussion of related research. Readers who can bene...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Hartfiel, Darald J. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1998.
Έκδοση:1st ed. 1998.
Σειρά:Lecture Notes in Mathematics, 1695
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03097nam a2200613 4500
001 978-3-540-68711-5
003 DE-He213
005 20191026121050.0
007 cr nn 008mamaa
008 121227s1998 gw | s |||| 0|eng d
020 |a 9783540687115  |9 978-3-540-68711-5 
024 7 |a 10.1007/BFb0094586  |2 doi 
040 |d GrThAP 
050 4 |a QA273.A1-274.9 
050 4 |a QA274-274.9 
072 7 |a PBT  |2 bicssc 
072 7 |a MAT029000  |2 bisacsh 
072 7 |a PBT  |2 thema 
072 7 |a PBWL  |2 thema 
082 0 4 |a 519.2  |2 23 
100 1 |a Hartfiel, Darald J.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Markov Set-Chains  |h [electronic resource] /  |c by Darald J. Hartfiel. 
250 |a 1st ed. 1998. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 1998. 
300 |a VIII, 132 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Lecture Notes in Mathematics,  |x 0075-8434 ;  |v 1695 
505 0 |a Stochastic matrices and their variants -- to Markov set-chains -- Convergence of Markov set-chains -- Behavior in Markov set-chains. 
520 |a In this study extending classical Markov chain theory to handle fluctuating transition matrices, the author develops a theory of Markov set-chains and provides numerous examples showing how that theory can be applied. Chapters are concluded with a discussion of related research. Readers who can benefit from this monograph are those interested in, or involved with, systems whose data is imprecise or that fluctuate with time. A background equivalent to a course in linear algebra and one in probability theory should be sufficient. 
650 0 |a Probabilities. 
650 0 |a Matrix theory. 
650 0 |a Algebra. 
650 0 |a Convex geometry . 
650 0 |a Discrete geometry. 
650 0 |a Biomathematics. 
650 0 |a Computer science-Mathematics. 
650 1 4 |a Probability Theory and Stochastic Processes.  |0 http://scigraph.springernature.com/things/product-market-codes/M27004 
650 2 4 |a Linear and Multilinear Algebras, Matrix Theory.  |0 http://scigraph.springernature.com/things/product-market-codes/M11094 
650 2 4 |a Convex and Discrete Geometry.  |0 http://scigraph.springernature.com/things/product-market-codes/M21014 
650 2 4 |a Mathematical and Computational Biology.  |0 http://scigraph.springernature.com/things/product-market-codes/M31000 
650 2 4 |a Math Applications in Computer Science.  |0 http://scigraph.springernature.com/things/product-market-codes/I17044 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783662179932 
776 0 8 |i Printed edition:  |z 9783540647751 
830 0 |a Lecture Notes in Mathematics,  |x 0075-8434 ;  |v 1695 
856 4 0 |u https://doi.org/10.1007/BFb0094586  |z Full Text via HEAL-Link 
912 |a ZDB-2-SMA 
912 |a ZDB-2-LNM 
912 |a ZDB-2-BAE 
950 |a Mathematics and Statistics (Springer-11649)