Statistical Inference for a Class of Startup Demonstration Tests

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Date

2019

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis inc

Open Access Color

Green Open Access

No

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Publicly Funded

No
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Average
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Average
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Top 10%

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Abstract

In this article, we develop a general statistical inference procedure for the probability of successful startup p in the case of startup demonstration tests when only the number of trials until termination of the experiment are observed. In particular, we define a class of startup demonstration tests and present expectation-maximization (EM) algorithm to get the maximum likelihood estimate of p for this class. Most of well-known startup testing procedures are involved in this class. Extension of the results to Markovian startups is also presented.

Description

Eryilmaz, Serkan/0000-0002-2108-1781

Keywords

EM algorithm, Markov chain, maximum likelihood estimation, phase-type distributions, reliability

Fields of Science

0211 other engineering and technologies, 02 engineering and technology, 0101 mathematics, 01 natural sciences

Citation

WoS Q

Q1

Scopus Q

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OpenCitations Citation Count
5

Source

Journal of Quality Technology

Volume

51

Issue

3

Start Page

314

End Page

324

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Citations

Scopus : 6

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Mendeley Readers : 6

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0.7024

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