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|a 0821845683 (acid-free paper)
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|a (ICU)BID18488563
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|a QA274.4
|b .H5313 1993
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| 082 |
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|a 519.2
|2 20
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| 100 |
1 |
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|a Hida, Takeyuki,
|d 1927-2017
|0 http://id.loc.gov/authorities/names/n86134240
|1 http://viaf.org/viaf/22219724
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| 240 |
1 |
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|a Gausu katei.
|l English
|
| 245 |
1 |
0 |
|a Gaussian processes /
|c Takeyuki Hida, Masuyuki Hitsuda ; translated by Takeyuki Hida and Masuyuki Hitsuda.
|
| 260 |
|
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|a Providence, R.I. :
|b American Mathematical Society,
|c c1993.
|
| 300 |
|
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|a xv, 183 p. ;
|c 27 cm.
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| 336 |
|
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|a text
|b txt
|2 rdacontent
|0 http://id.loc.gov/vocabulary/contentTypes/txt
|
| 337 |
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|a unmediated
|b n
|2 rdamedia
|0 http://id.loc.gov/vocabulary/mediaTypes/n
|
| 338 |
|
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|a volume
|b nc
|2 rdacarrier
|0 http://id.loc.gov/vocabulary/carriers/nc
|
| 440 |
|
0 |
|a Translations of mathematical monographs
|v v. 120
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| 500 |
|
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|a Translation of: Gausu katei.
|
| 504 |
|
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|a Includes bibliographical references (p. 177-179) and index.
|
| 505 |
0 |
0 |
|g Ch. I.
|t Foundations of Probability Theory and Limit Theorems.
|g 1.
|t Probability spaces and random variables.
|g 2.
|t Probability distributions of random variables (random vectors) and characteristic functions.
|g 3.
|t Convergence of sequences of random variables.
|g 4.
|t Limit theorems for sums of independent random variables.
|g 5.
|t Conditional expectations and martingales.
|g 6.
|t Measures on function spaces (measures induced from stochastic processes) --
|g Ch. II.
|t Systems of Gaussian Random Variables.
|g 2.
|t Some important properties of a Gaussian system.
|g 3.
|t Complex Gaussian systems.
|g 4.
|t Discrete parameter Gaussian processes: Canonical representation.
|g 5.
|t Continuous parameter Gaussian processes: Brownian motion --
|g Ch. III.
|t Stationary Gaussian Processes and Their Representations.
|g 1.
|t Discrete parameter stationary processes.
|g 2.
|t Spectral representation of a stationary Gaussian process.
|g 3.
|t Canonical representation of stationary processes I: The discrete parameter case.
|g 4.
|t Canonical representation of stationary processes II: The continuous parameter case --
|g Ch. IV.
|t Canonical Representation of Gaussian Processes: General Theory and Multiplicity.
|g 1.
|t Propagation of random phenomena.
|g 2.
|t Canonical representation and multiplicity.
|g 3.
|t Gaussian processes and reproducing kernel Hilbert spaces.
|g 4.
|t Examples of a canonical representation and a noncanonical one.
|g 5.
|t Application to prediction theory --
|g Ch. V.
|t Multiple Markov Gaussian Processes.
|g 1.
|t Multiple Markov processes with discrete parameter.
|g 2.
|t Multiple Markov Gaussian processes with continuous parameter.
|g 3.
|t Multiple Markov Gaussian processes in the restricted sense.
|g 4.
|t Multiple Markov stationary Gaussian processes.
|g 5.
|t Levy's M(t)-process.
|g 6.
|t T-positivity --
|g Ch. VI.
|t Equivalence of Gaussian Processes.
|g 1.
|t Setting up the problem.
|g 2.
|t General theory of equivalence of Gaussian measures.
|g 3.
|t Equivalence of Gaussian processes with discrete parameter.
|g 4.
|t Canonical representations of Gaussian processes equivalent to Wiener processes.
|g 5.
|t Canonical representation of Gaussian processes equivalent to a given Gaussian process.
|g 6.
|t Constructing innovation processes.
|t Appendix. Stochastic Integrals and Martingales.
|g 1.
|t Multiple Wiener integrals.
|g 2.
|t Martingales and stochastic (Ito) integrals.
|g 3.
|t Ito's formula and Girsanov's theorem.
|
| 650 |
|
0 |
|a Gaussian processes
|0 http://id.loc.gov/authorities/subjects/sh85053558
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| 650 |
|
7 |
|a Gaussian processes.
|2 fast
|0 http://id.worldcat.org/fast/fst00939020
|
| 700 |
1 |
0 |
|a Hitsuda, Masuyuki,
|d 1938-
|0 http://id.loc.gov/authorities/names/n92082719
|1 http://viaf.org/viaf/108504042
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| 850 |
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|t Library of Congress classification
|a QA274.4.H53130 1993
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|t Library of Congress classification
|a QA274.4.H53130 1993
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|c JCL-Sci
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