000			01394cam a2200229 4500
008			720504s19641962cauaaaagrb 001 0 eng
040			_aDLC _cDLC
050	0	0	_aQA273 _b.P278
082	0	0	_a519.1 _bPAR
100	1		_aParzen, Emanuel.
245	1	0	_aStochastic Processes /
260			_aSan Francisco : _bHolden-Day, _c[1964, c1962].
300			_a324 p.:ill,
440			_aHolden-Day Series in Probability and Statistics edited by Lehman, E. L. /
504			_aIncludes bibliographical references: p. [307]-313 and indexes: p. [3140-324.
520			_aThe theory of Stochastic Processes is generally defined as the "dynamic" part of probability theory, in which one studies a collection of random variables (called stochastic process) from the point of view of their interdependence and limiting behavior. This course has three main aims: 1) to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models; 2) to provide an introduction to the methods of probability model-building; and 3) to provide the reader who does not possess an advanced mathematical background with mathematically sound techniques and with a sufficient degree of maturity to enable further study of the theory of stochastic processes.
590			_ane 23/03/2018
591			_aLoan
650		0	_aProbabilities.
942			_2ddc _cBOOK
949			_a519.1 PAR
999			_c7584 _d7584