000			01491nam a22001697a 4500
999			_c65618 _d65618
008			200611b2019 ||||| |||| 00| 0 eng d
020			_a9781108473682
082			_a519.2 DUR-R
100			_aDurrett, Rick
245			_aProbability : _btheory and examples / _cRick Durrett
250			_a5th ed.
260			_aUnited KIngdom _bCambridge University Press _c2019
300			_a419 p.
365			_aGBP _b59.99.
500			_aThis lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.
650			_aProbabilities