Foundations of Stochastic Analysis
ଅପ୍ରେଲ 2013 · Courier Corporation
ଇବୁକ୍
320
ପୃଷ୍ଠାଗୁଡ଼ିକ
reportରେଟିଂ ଓ ସମୀକ୍ଷାଗୁଡ଼ିକୁ ଯାଞ୍ଚ କରାଯାଇନାହିଁ ଅଧିକ ଜାଣନ୍ତୁ
ଏହି ଇବୁକ୍ ବିଷୟରେ
Stochastic analysis involves the study of a process involving a randomly determined sequence of observations, each of which represents a sample of one element of probability distribution. This volume considers fundamental theories and contrasts the natural interplay between real and abstract methods.
Starting with the introduction of the basic Kolmogorov-Bochner existence theorem, the text explores conditional expectations and probabilities as well as projective and direct limits. Subsequent chapters examine several aspects of discrete martingale theory, including applications to ergodic theory, likelihood ratios, and the Gaussian dichotomy theorem. Prerequisites include a standard measure theory course. No prior knowledge of probability is assumed; therefore, most of the results are proved in detail. Each chapter concludes with a problem section that features many hints and facts, including the most important results in information theory.
Starting with the introduction of the basic Kolmogorov-Bochner existence theorem, the text explores conditional expectations and probabilities as well as projective and direct limits. Subsequent chapters examine several aspects of discrete martingale theory, including applications to ergodic theory, likelihood ratios, and the Gaussian dichotomy theorem. Prerequisites include a standard measure theory course. No prior knowledge of probability is assumed; therefore, most of the results are proved in detail. Each chapter concludes with a problem section that features many hints and facts, including the most important results in information theory.
ଲେଖକଙ୍କ ବିଷୟରେ
M. M. Rao is a Professor in the Department of Mathematics at the University of California, Riverside.
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