THE POISSON DISTRIBUTION AND POISSON PROCESS IN PSYCHOMETRIC THEORY1
نویسندگان
چکیده
منابع مشابه
The Poisson-Dirichlet Distribution And The Scale-Invariant Poisson Process
We show that the Poisson–Dirichlet distribution is the distribution of points in a scale-invariant Poisson process, conditioned on the event that the sum T of the locations of the points in (0,1] is 1. This extends to a similar result, rescaling the locations by T , and conditioning on the event that T 6 1. Restricting both processes to (0, β] for 0 < β 6 1, we give an explicit formula for the ...
متن کاملThe Exponentiated Poisson-Lindley Distribution; Features and Applications in Reliability
Abstract. In this paper a new three-parameter lifetime distribution named “the Exponentialed Lindley-Poisson (E-LP) distribution” has been suggested that it has an increasing, decreasing and invers bathtube hazard rate depending on the parameter values. The (E-LP) distribution has applications in economics, actuarial modeling, reliability modeling, lifetime and queuing problems and biological ...
متن کاملFractional Poisson Process
For almost two centuries, Poisson process with memoryless property of corresponding exponential distribution served as the simplest, and yet one of the most important stochastic models. On the other hand, there are many processes that exhibit long memory (e.g., network traffic and other complex systems). It would be useful if one could generalize the standard Poisson process to include these p...
متن کاملApplication of Gompertz-Poisson Distribution in LifetimeTheory
Gompertz-Poisson distribution is a three-parameter lifetime distribution with increasing, decreasing, increasing-decreasing and unimodal shape failure rate function and a composition of Gompertz and Poisson distributions cut at zero point that in this paper estimated the parameters of the distribution by maximum likelihood method and in order to confirm the calculated estimates, based on random...
متن کاملThe Exponential Distribution & Poisson Process 1
We finished discussing Discrete-Time Markov Chains in the previous lecture, and are now heading towards Continuous-Time Markov Chains. Discrete-time Markov Chains are totally synchronized, whereas CTMCs are not. In preparation for CTMCs, we need to discuss the Exponential distribution and the Poisson arrival process. We say that a random variable X is distributed exponentially with rate λ, X ∼ ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ETS Research Bulletin Series
سال: 1968
ISSN: 0424-6144
DOI: 10.1002/j.2333-8504.1968.tb00565.x