Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Arun Kaushik"'
Autor:
Aashiq Ahamed Shukkoor, Nimmy Elizabeth George, Shanmugasundaram Radhakrishnan, Sivakumar Velusamy, Rajendiran Gopalan, Tamilarasu Kaliappan, Premkrishna Anandan, Ramasamy Palanimuthu, Vidhyakar Balasubramaniam, Vinoth Doraiswamy, Arun Kaushik Ponnusamy
Publikováno v:
The Egyptian Heart Journal, Vol 73, Iss 1, Pp 1-10 (2021)
Abstract Background The epidemiology of HF in India is largely unexplored. Current resources are based on a few hospital-based and a community-based registry from North India. Thus, we present the data from a single hospital-based registry in South I
Externí odkaz:
https://doaj.org/article/aa34509024a2469999444165e09dac94
Publikováno v:
Austrian Journal of Statistics, Vol 50, Iss 1 (2021)
The aim of this paper is to present the estimation procedure for the step-stress partially accelerated life test model under the generalized progressive hybrid censoring scheme. The uncertainties are assumed to be governed by Lindley distribution. Th
Externí odkaz:
https://doaj.org/article/7faeeea114164cd19be8530fbccce73b
Publikováno v:
Austrian Journal of Statistics, Vol 50, Iss 1 (2021)
In this article, we considered the statistical inference for the unknown parameters of exponentiated exponential distribution based on a generalized progressive hybrid censored sample under classical paradigm. We have obtained maximum likelihood esti
Externí odkaz:
https://doaj.org/article/a6463e0cda0e4e4ba256f8d30d0814f8
Autor:
Arun Kaushik
Publikováno v:
Austrian Journal of Statistics, Vol 48, Iss 3 (2019)
In this paper, we have considered the problem of optimal inspection times for the progressive interval type-I censoring scheme where uncertainty in the process is governed by the two-parameter Rayleigh distribution. Here, we also introduced some opti
Externí odkaz:
https://doaj.org/article/7ddca5ad79d64c42abee5ef441008850
Publikováno v:
Austrian Journal of Statistics, Vol 47, Iss 1 (2018)
This paper deals with the estimation procedure for inverse Weibull distribution under progressive type-II censored samples when removals follow Beta-binomial probability law. To estimate the unknown parameters, the maximum likelihood and Bayes estima
Externí odkaz:
https://doaj.org/article/f357de50086f4f318e538271ad82a8d4
Publikováno v:
Austrian Journal of Statistics, Vol 46, Iss 2 (2017)
The present article aims to point and interval estimation of the parameters of generalised exponential distribution (GED) under progressive interval type-I (PITI) censoring scheme with random removals. The considered censoring scheme is most useful i
Externí odkaz:
https://doaj.org/article/2436f53ea5e241d88bb1b78da262b818
Autor:
Unnati Nigam, Arun Kaushik
Publikováno v:
G Families of Probability Distributions ISBN: 9781003232193
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5268f35a3781e8e28793ed75ae2405c6
https://doi.org/10.1201/9781003232193-20
https://doi.org/10.1201/9781003232193-20
Autor:
Sumanth Gandra, Sanjeev Singh, Murali Chakravarthy, Merlin Moni, Pruthu Dhekane, Zubair Mohamed, Anil Kumar, Arun Kaushik, Fathima Shameen, Priyadarshini Senthil, Tejaswini Saravanan, Anu George, Dorothy Sinclair, Dustin Stwalley, Jacaranda van Rheenen, Matthew Westercamp, Rachel Mann Smith, Surbhi Leekha, David K Warren
Publikováno v:
Open Forum Infectious Diseases. 9
Background The National Healthcare Safety Network (NHSN) central line-associated bloodstream infection (CLABSI) is a widely accepted quality measure. However, studies from the United States indicate that NHSN reportable CLABSIs account for less than
Autor:
Arun Kaushik, Anil K. Gupta, Steven C. Clemens, Pankaj Kumar, Prasanta Sanyal, Priyantan Gupta, Manoj Kumar Jaiswal, Abhayanand S. Maurya, Sreya Sengupta, Rajveer Sharma, Rahul Pawar
Publikováno v:
Palaeogeography, Palaeoclimatology, Palaeoecology. 619:111544
Autor:
Seema Raj, Manish Kumar, Anjali Chauhan, Arun Kaushik, Dinesh Kumar, Aarti Gangadhar Shinde, Nidhi Bansal, Chhavi Kaushik, Hunny
Publikováno v:
International Journal of Technical Research & Science. :119-130