This is the only book discussing multifractal properties of densities of stable superprocesses, containing latest achievements while also giving the reader a comprehensive picture of the state of the art in this area. It is a self-contained presentation of regularity properties of stable superprocesses and proofs of main results and can serve as an introductory text for a graduate course. There are many heuristic explanations of technically involved results and proofs and the reader can get a clear intuitive picture behind the results and techniques.
This is the only book discussing multifractal properties of densities of stable superprocesses, containing latest achievements while also giving the reader a comprehensive picture of the state of the art in this area. It is a self-contained presentation of regularity properties of stable superprocesses and proofs of main results and can serve as an introductory text for a graduate course. There are many heuristic explanations of technically involved results and proofs and the reader can get a clear intuitive picture behind the results and techniques.
Produktdetails
Produktdetails
SpringerBriefs in Probability and Mathematical Statistics
Introduction, main results and discussion.- Stochastic representation for X and description of the approach for determining regularity.- Some simple properties of (2;d;b )-superprocesses.- Analysis of jumps of superprocesses.- Dichotomy for densities.- Pointwise Hölder exponent at a given point: proof of Theorem 1.3.- Elements of the proof of Theorem 1.5 and Proposition 1.6.- A Estimates for the transition kernel of the one-dimensional Brownian motion.- B Probability inequalities for a spectrally positive stable process.- References.
Introduction, main results and discussion.- Stochastic representation for X and description of the approach for determining regularity.- Some simple properties of (2;d;b )-superprocesses.- Analysis of jumps of superprocesses.- Dichotomy for densities.- Pointwise Hölder exponent at a given point: proof of Theorem 1.3.- Elements of the proof of Theorem 1.5 and Proposition 1.6.- A Estimates for the transition kernel of the one-dimensional Brownian motion.- B Probability inequalities for a spectrally positive stable process.- References.
Introduction, main results and discussion.- Stochastic representation for X and description of the approach for determining regularity.- Some simple properties of (2;d;b )-superprocesses.- Analysis of jumps of superprocesses.- Dichotomy for densities.- Pointwise Hölder exponent at a given point: proof of Theorem 1.3.- Elements of the proof of Theorem 1.5 and Proposition 1.6.- A Estimates for the transition kernel of the one-dimensional Brownian motion.- B Probability inequalities for a spectrally positive stable process.- References.
Introduction, main results and discussion.- Stochastic representation for X and description of the approach for determining regularity.- Some simple properties of (2;d;b )-superprocesses.- Analysis of jumps of superprocesses.- Dichotomy for densities.- Pointwise Hölder exponent at a given point: proof of Theorem 1.3.- Elements of the proof of Theorem 1.5 and Proposition 1.6.- A Estimates for the transition kernel of the one-dimensional Brownian motion.- B Probability inequalities for a spectrally positive stable process.- References.
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