Poisson process and distribution-free statistics
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 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 کاملPoisson Statistics
Prior scientific knowledge has shown that the radioactive decay of nuclei can be modeled as a series of independent, random events. [1] The probability for the occurence of such events can thus be modeled by Poisson statistics. In this experiment, we studied the radioactive decay of Cs by using a NaI scintillator. We recorded the counts per second for 100 consecutive one-second long intervals a...
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 کاملDistribution Free Confidence Intervals for Quantiles Based on Extreme Order Statistics in a Multi-Sampling Plan
Extended Abstract. Let Xi1 ,..., Xini ,i=1,2,3,....,k be independent random samples from distribution $F^{alpha_i}$، i=1,...,k, where F is an absolutely continuous distribution function and $alpha_i>0$ Also, suppose that these samples are independent. Let Mi,ni and M'i,ni respectively, denote the maximum and minimum of the ith sa...
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: Advances in Applied Probability
سال: 1974
ISSN: 0001-8678,1475-6064
DOI: 10.2307/1426298