Structural and Statistical Problems for a Class of Stochastic Processes (eBook)

The First Samuel Stanley Wilks Lecture at Princeton University, March 7, 1970

Harald Cramer (Autor)

eBook Download: PDF

2017
32 Seiten
Princeton University Press (Verlag)
978-1-4008-8586-2 (ISBN)

Infos

Professor Cramer, author of the pivotal Mathematical Methods of Statistics (1946), examines problems in the theory of stochastic processes that can be considered as generalizations of problems in the classical theory of statistical inference. He discusses first the representation formula and then treats its application to the multiplicity problem, classes of processes with multiplicity N= 1, normal or Gaussian processes. He concludes with a discussion of problems of estimation for a normal process. A distinguished mathematician, Harald Cramer has been President of the University of Stockholm and Chancellor of the Swedish Universities. He is a member of many professional societies, including the Royal Swedish Academy of Science and the American Academy of Arts and Sciences.Originally published in 1971.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Produkt-Details

• Erscheint lt. Verlag: 14.3.2017
• Reihe/Serie: Princeton Legacy Library
• Reihe/Serie: Princeton Legacy Library
• Verlagsort: Princeton
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Schlagworte: absolute continuity • Addition • Almost surely • Alternative hypothesis • Calculation • Certainty • Constant function • correlation coefficient • Covariance function • Cyclic subspace • Derivative • diagonal • Dirac delta function • Disjoint sets • Eigenfunction • Eigenvalues and Eigenvectors • electric current • Equation • equivalence class • existential quantification • Finite-dimensional distribution • hilbert space • inference • integral equation • Iteration • Joint probability distribution • Least Squares • Likelihood-ratio test • Linear combination • Linear least squares (mathematics) • Markov process • Mathematical Statistics • Natural number • Neyman–Pearson lemma • Normal distribution • Parameter • partial derivative • partially ordered set • Prediction • Probability • Probability Distribution • probability measure • Probability space • Projection (linear algebra) • quadratic variation • Radon–Nikodym theorem • Random Variable • real number • representation theorem • reproducing kernel Hilbert space • Root mean square • Special case • stationary process • Statistic • Statistical hypothesis testing • Statistical Inference • Statistical Science • statistician • Statistics • Stochastic Calculus • Stochastic process • Summation • Theorem • theory • Ulf Grenander • uniqueness • Variance • Volterra integral equation • Wiener process • year • Zero element
• ISBN-10: 1-4008-8586-8 / 1400885868
• ISBN-13: 978-1-4008-8586-2 / 9781400885862