Generalized Waiting Time Distributions Associated With Runs

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2016

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Springer Heidelberg

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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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Abstract

Let be a {X-t, t >= 1} sequence of random variables with two possible values as either "1" (success) or "0" (failure). Define an independent sequence of random variables {D-i, i >= 1}. The random variable is associated with the success when it occupies the ith place in a run of successes. We define the weight of a success run as the sum of the D values corresponding to the successes in the run. Define the following two random variables: is the number of trials until the weight of a single success run exceeds or equals k, and is the number of trials until the weight of each of r success runs equals or exceeds k in {X-t, t >= 1}. Distributional properties of the waiting time random variables and are studied and illustrative examples are presented.

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Eryilmaz, Serkan/0000-0002-2108-1781
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6

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Volume

79

Issue

3

Start Page

357

End Page

368

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https://doi.org/10.1007/s00184-015-0558-4
 https://hdl.handle.net/20.500.14411/467

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