Cantitate/Preț
Produs

Exercises and Solutions Manual for Integration and Probability: by Paul Malliavin

Autor Gerard Letac Traducere de L. Kay
en Limba Engleză Paperback – 12 iun 1995
This book presents the problems and worked-out solutions for all the exercises in the text by Malliavin. It will be of use not only to mathematics teachers, but also to students using the text for self-study.
Citește tot Restrânge

Preț: 45827 lei

Preț vechi: 79500 lei
-42%

Puncte Express: 687

Carte indisponibilă temporar

Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.

Specificații

ISBN-13: 9780387944210
ISBN-10: 0387944214
Pagini: 142
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.27 kg
Ediția:1995
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

I Measurable Spaces and Integrable Functions.- 1 ?-algebras and partitions.- 2 r-families.- 3 Monotone classes and independence.- 4 Banach limits.- 5 A strange probability measure.- 6 Integration and distribution functions.- 7 Evaluating $$ \sum\nolimits_{n = 1}^\infty {\frac{{{{\left( { - 1} \right)}^n}}}{{{n^2}}}} $$.- 8 Monotone convergence.- 9 Vector integration.- 10 Convergence in measure and composition of functions.- 11 Principle of separation of variables.- 12 The Cauchy-Schwarz inequality.- 13 Test that X ? Y almost everywhere.- 14 Image of a measure.- 15 Primitives of square integrable functions.- II Borel Measures and Radon Measures.- 1 Positive measures on an open interval.- 2 Distribution functions.- 3 Convexity and growth.- 4 Convexity and measure.- 5 Integral representation of positive convex functions (0, ?).- 6 Integral representations of Askey functions.- 7 Gauss’s inequality.- 8 Integral of a decreasing function.- 9 Second mean value theorem for integrals.- 10 Variance of a distribution on [0, 1].- 11 Variance of the distribution of a convex function on [0, 1].- 12 Rational functions which preserve Lebesgue measure.- 13 A measure on the half-plane.- 14 Weak convergence and moments.- 15 Improper integrals and Lebesgue measure.- 16 $$ \int_0^\infty {\frac{{\sin x}}{x}} dx,\int_0^\infty {\left( {\cos ax - \cos bx} \right)} \frac{{dx}}{x},\int_0^\infty {\left( {\cos ax - \cos bx} \right)} \frac{{dx}}{{{x^2}}} $$.- 17 Comparisons between different Lp spaces.- 18 Differentiation under the integral sign.- 19 Laplace transform of a measure on [0,+?).- 20 Comparison of vague, weak, and narrow convergence.- 21 Weak compactness of measures.- 22 Vague convergence and limit of µn (0).- 23 Vague convergence and restriction to a closed set.- 24 Change of variables in an integral.- 25 Image of a measure and the Jacobian.- III Fourier Analysis.- 1 Characterizations of radial measures.- 2 Radial measures and independence.- 3 Area of the sphere.- 4 Fourier transform of the Poisson kernel of R+n+1.- 5 Askey-Polya functions.- 6 Symmetric convex sets in the plane and measures on [0,?).- 7 T. Ferguson’s theorem.- 8 A counterexample of Herz.- 9 Riesz kernels.- 10 Measures on the circle and holomorphic functions.- 11 Harmonic polynomials and the Fourier transform.- 12 Bernstein’s inequality.- 13 Cauchy’s functional equation.- 14 Poisson’s formula.- 15 A list of Fourier-Plancheral transforms.- 16 Fourier-Plancheral transform of a rational function.- 17 Computing some Fourier-Plancheral transforms.- 18 Expressing the Fourier-Plancheral transform as a limit.- 19 An identity for the Fourier-Plancheral transform.- 20 The Hilbert transform on L2(R).- 21 Action of L1(R) on L2(R).- 22 Another expression for the Hilbert transform.- 23 A table of properties of the Hilbert transform.- 24 Computing some Hilbert transforms.- 25 The Hilbert transform and distributions.- 26 Sobolev spaces on R.- 27 H. Weyl’s inequality.- IV Hilbert Space Methods and Limit Theorems in Probability Theory.- 1 Fancy dice.- 2 The geometric distribution.- 3 The binomial and Poisson distributions.- 4 Construction of given distributions.- 5 Von Neumann’s method.- 6 The laws of large numbers.- 7 Etemadi’s method.- 8 A lemma on the random walks Sn.- 9 ?(s) = limn?? (P[Sn ? s·n])1/n exists.- 10 Evaluating ?(s) in some concrete cases.- 11 Algebra of the gamma and beta distributions.- 12 The gamma distribution and the normal distribution.- 13 The Cauchy distribution and the normal distribution.- 14 A probabilistic proof of Stirling’s formula.- 15 Maxwell’s theorem.- 16 If X1 and X2 are independent, then $$\frac{{\left( {{x_1},{x_2}} \right)}}{{{{\left( {x_1^2 + x_2^2} \right)}^{1/2}}}}$$ is uniform.- 17 Isotropy of pairs and triplets of independent variables.- 18 The only invertible distributions are concentrated at a point.- 19 Isotropic multiples of normal distributions.- 20 Poincaré’s lemma.- 21 Schoenberg’s theorem.- 22 A property of radial distributions.- 23 Brownian motion hits a hyperplane in a Cauchy distribution.- 24 Pittinger’s inequality.- 25 Cylindrical probabilities.- 26 Minlos’s lemma.- 27 Condition that a cylindrical probability be a probability measure.- 28 Lindeberg’s theorem.- 29 H. Chernoff’s inequality.- 30 Gebelein’s inequality.- 31 Fourier transform of the Hermite polynomials.- 32 Another definition of conditional expectation.- 33 Monotone continuity of conditional expectations.- 34 Concrete computation of conditional expectations.- 35 Conditional expectations and independence.- 36 E(X|Y) = Y and E(Y|X) = X.- 37 Warnings about conditional expectations.- 38 Conditional expectations in the absolutely continuous case and the Gaussian case.- 39 Examples of martingales.- 40 A reversed martingale.- 41 A probabilistic approximation of an arithmetic conjecture.- 42 A criterion for uniform integrability.- 43 The Galton-Watson process and martingales.- V Gaussian Sobolev Spaces and Stochastic Calculus of Variations.- 1 d and ? cannot both be continuous.- 2 Growth of the Hermite polynomials.- 3 Viskov’s lemma.- 4 Cantelli’s conjecture.- 5 Lancaster probabilities in R2.- 6 Sarmanov’s theorem.