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pro vyhledávání: '"Banerjee, Buddhananda"'
In many temporal datasets, the parameters of the underlying distribution may change abruptly at unknown times. Detecting these changepoints is crucial for numerous applications. While this problem has been extensively studied for linear data, there h
Externí odkaz:
http://arxiv.org/abs/2409.08838
Autor:
Banerjee, Buddhananda, Biswas, Surojit
This paper introduces a dependent toroidal distribution, to analyze astigmatism data following cataract surgery. Rather than utilizing the flat torus, we opt to represent the bivariate angular data on the surface of a curved torus, which naturally of
Externí odkaz:
http://arxiv.org/abs/2409.06229
Autor:
Biswas, Surojit, Banerjee, Buddhananda
A generic family of distributions, defined on the surface of a curved torus is introduced using the area element of it. The area uniformity and the maximum entropy distribution are identified using the trigonometric moments of the proposed family. A
Externí odkaz:
http://arxiv.org/abs/2405.09149
In many temporally ordered data sets, it is observed that the parameters of the underlying distribution change abruptly at unknown times. The detection of such changepoints is important for many applications. While this problem has been studied subst
Externí odkaz:
http://arxiv.org/abs/2403.00508
Autor:
Banerjee, Buddhananda, Biswas, Surojit
The distributions of toroidal data, often viewed as an extension of circular distributions, do not consider the intrinsic geometry of a curved torus. For the first time, Diaconis et al. (2013)[Diaconis, P., Holmes, S., & Shahshahani, M. (2013). Sampl
Externí odkaz:
http://arxiv.org/abs/2304.01599
In machine learning, a routine practice is to split the data into a training and a test data set. A proposed model is built based on the training data, and then the performance of the model is assessed using test data. Usually, the data is split rand
Externí odkaz:
http://arxiv.org/abs/2206.11721
In this paper we propose an epidemiological model for the spread of COVID-19. The dynamics of the spread is based on four fundamental categories of people in a population: Tested and infected, Non-Tested but infected, Tested but not infected, and non
Externí odkaz:
http://arxiv.org/abs/2006.06404
Functional data often arise as sequential temporal observations over a continuous state-space. A set of functional data with a possible change in its structure may lead to a wrong conclusion if it is not taken in to account. So, sometimes, it is cruc
Externí odkaz:
http://arxiv.org/abs/1503.05130
Akademický článek
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Autor:
Banerjee, Buddhananda1,2 (AUTHOR) bbanerjee@maths.iitkgp.ac.in, Laha, Arnab K.3 (AUTHOR), Lakra, Arjun1 (AUTHOR)
Publikováno v:
Statistical Analysis & Data Mining. Dec2020, Vol. 13 Issue 6, p529-536. 8p.
