Titlebook: Applied Probability; Kenneth Lange Textbook 20102nd edition The Editor(s) (if applicable) and The Author(s), under exclusive license to Sp

遺留之物

土產(chǎn)

Egbert K. Duursma,JoLynn Carrolleady aware of the clever applications of characteristic and moment generating functions. This chapter is intended to review and extend some of the tools that probabilists routinely call on. Readers can consult the books [34, 59, 60, 78, 80, 166] for many additional examples of these tools in action.

組裝

Land-Use Change as a Disturbance Regime,rocesses stress one-dimensional processes. This is unfortunate because many of the important applications occur in higher dimensions, and the underlying theory is about as simple there. In this chapter, we emphasize multidimensional Poisson processes, their transformation properties, and computational tools for extracting information about them.

凹處

musicologist

Calculation of Expectations,eady aware of the clever applications of characteristic and moment generating functions. This chapter is intended to review and extend some of the tools that probabilists routinely call on. Readers can consult the books [34, 59, 60, 78, 80, 166] for many additional examples of these tools in action.

強(qiáng)壯

Poisson Processes,rocesses stress one-dimensional processes. This is unfortunate because many of the important applications occur in higher dimensions, and the underlying theory is about as simple there. In this chapter, we emphasize multidimensional Poisson processes, their transformation properties, and computational tools for extracting information about them.

有說服力

Branching Processes,spring contributing to the next generation. The key assumption that drives the theory is that particles reproduce independently according to the same probabilistic law. Interactions between particles are forbidden.

ANT

Environmental Concerns and Remediationve some probability model for generating typical problems on which the algorithm operates. The examples in this chapter on sorting, data compression, and graph coloring illustrate some of the underlying models and the powerful techniques probabilists have created for analyzing algorithms.

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