'Counting process' diaporamas de présentation

Assume the model:

Borgan and Henderson: Event History Methodology Lancaster, September 2006 Session 2: Nelson-Aalen, Kaplan-Meier and Aalen-Johansen estimators. Nelson-Aalen estimator. Assume the model:. at risk indicator. common hazard/intensity (non-negative function).

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The Poisson Process

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Counting Process: State of the system is given by the total number of customers in the system .

Counting Process: State of the system is given by the total number of customers in the system. c ont. N(t)=state of system at time t . (1) N(0)=0 (2) events are independant if they relate to non-overlapping intervals. 4pm. 5pm. 6pm. (3) stationary process :

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Strong Invariance Principle for Randomly Stopped Stochastic Processes

Strong Invariance Principle for Randomly Stopped Stochastic Processes. Andrii Andrusiv, Nadiia Zinchenko. Introduction. Let be sequence of non-negative i.i.d.r.v. with d.f. and ch.f. , Denote

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Today I will: Explain Significance in Measurement Take proper measurements

Today I will: Explain Significance in Measurement Take proper measurements . Significance in Measurement. Measurements always involve a comparison . When you say that a table is 6 feet long, you're really saying that the table is six times longer than an object that is 1 foot long.

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Special Sets of Numbers

Special Sets of Numbers. Remember to Silence Your Cell Phone and Put It In Your Bag!. Mathematics was invented. Numbers vs. numerals. The Set of Counting Numbers or Natural Numbers. N = {1, 2, 3, 4, 5, . . . } The Counting Process Say the names of the counting numbers Name the numerals

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Classification of Variables

Classification of Variables. Discrete Numerical Variable A variable that produces a response that comes from a counting process . Classification of Variables. Continuous Numerical Variable A variable that produces a response that is the outcome of a measurement process .

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