Zobrazeno 1 - 10
of 35
pro vyhledávání: '"G, Hareesh"'
We propose a modified weighted Nadaraya-Watson estimator for the conditional distribution of a time series with heavy tails. We establish the asymptotic normality of the proposed estimator. Simulation study is carried out to assess the performance of
Externí odkaz:
http://arxiv.org/abs/2407.15564
Publikováno v:
Saudi Journal of Kidney Diseases and Transplantation, Vol 30, Iss 5, Pp 1058-1064 (2019)
Arteriovenous fistula (AVF) is the most appropriate vascular access for all chronic kidney disease patients for hemodialysis. However, patients with diabetic nephropathy are at increased risk for primary failure after AVF creation, mainly due to athe
Externí odkaz:
https://doaj.org/article/7ba5959fb9ef47ffb693fb46c34f0926
Publikováno v:
International Journal for Research in Applied Science and Engineering Technology. 11:1482-1490
In order to address environmental issues, the automotive industry is moving in a significant direction towards hybrid vehicles. One of its primary drive system options is a switching reluctance motor (SRM). This article designs a brand-new SRM conver
Publikováno v:
OCEANS 2022, Hampton Roads.
Publikováno v:
OCEANS 2022, Hampton Roads.
Publikováno v:
OCEANS 2022 - Chennai.
Publikováno v:
Journal of the Korean Statistical Society. 49:578-595
Entropy based dependence measures are used as an alternative to correlation for determining the lag dependency of time series models. In this study, we explore the properties of partial autoinformation function (PAIF) to identify the lag dependency o
Autor:
Ashok. M., G. Hareesh Kumar
Publikováno v:
International Journal of Trend in Scientific Research and Development. 2:1401-1406
Educational data mining emphasizes on developing algorithms and new tools for identifying distinctive sorts of data that come from educational settings, to better understand students. The objective of this paper is to cluster efficient students among
Autor:
N. Balakrishna, G. Hareesh
Publikováno v:
Statistics. 52:288-302
This paper develops algorithms for fitting autoregressive models with symmetric stable innovations using auto-covariation function. A recursive algorithm is proposed for generalized Yule-Walker est...
Akademický článek
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