An Introduction to Stochastic Processes: With Special Reference to Methods and Applications
Random sequences; Processes in continuous time; Miscellaneous statistical applications; Limiting stochastic operations; Stationary processes; Prediction and communication theory; The statistical analysis of stochastic processes; Correlation analysis of time-series.
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additive alternative analysis applications approximately arise assumed asymptotic average becomes chance Chapter characteristic coefficients complete component condition consider constant continuous convenient convergence correlation corresponding course defined denotes density depend differential discrete discussed distribution effect equation equivalent estimate example exists expected expression extended finite follows formula frequency function further given gives Hence hold implies important increases independent individual initial integral interval limiting linear Markov chain matrix mean methods normal observed obtain occurring operator original particular population possible probability problem properties quantity random recurrence referred relation renewal representing respect result roots sampling sequence shown simple solution specified spectral spectrum stationary processes statistical stochastic processes suppose theoretical theory tion transition true values variable variance vector whence write zero