Structural and Statistical Problems for a Class of Stochastic Processes
Harald Cramér
* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Naturwissenschaften, Medizin, Informatik, Technik / Mathematik
Beschreibung
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.
Kundenbewertungen
Likelihood-ratio test, Partial derivative, Dirac delta function, Statistical inference, Finite-dimensional distribution, Stationary process, Uniqueness, Cyclic subspace, Mathematical statistics, Derivative, Parameter, Probability distribution, Diagonal, Constant function, Eigenfunction, Root mean square, Statistic, Representation theorem, Projection (linear algebra), Volterra integral equation, Certainty, Disjoint sets, Hilbert space, Statistical Science, Wiener process, Reproducing kernel Hilbert space, Existential quantification, Alternative hypothesis, Statistics, Joint probability distribution, Neyman–Pearson lemma, Integral equation, Statistician, Linear combination, Absolute continuity, Zero element, Addition, Equivalence class, Normal distribution, Inference, Markov process, Theorem, Covariance function, Statistical hypothesis testing, Almost surely, Prediction, Random variable, Iteration, Probability, Stochastic calculus, Quadratic variation, Calculation, Linear least squares (mathematics), Radon–Nikodym theorem, Partially ordered set, Probability measure, Special case, Correlation coefficient, Stochastic process, Least squares, Real number, Theory, Equation, Ulf Grenander, Summation, Natural number, Variance, Year, Probability space, Eigenvalues and eigenvectors