Author

# Arindam Sengupta

Bio: Arindam Sengupta is an academic researcher from University of Calcutta. The author has contributed to research in topic(s): Random variable & Natural filtration. The author has an hindex of 5, co-authored 15 publication(s) receiving 56 citation(s). Previous affiliations of Arindam Sengupta include Indian Statistical Institute & Indian Institute of Technology Guwahati.
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Journal ArticleDOI
Abstract: Asymptotic tests for identical distribution of responses in two independent sets of Likert-type scale data using latent variable models are developed. The proposed tests are compared with regard to...

Journal ArticleDOI
01 Jun 2017
Abstract: Convergence of a sequence of stochastic processes obtained from Likert-Type scaling with increasing number of categories with increasing sample sizes is considered. Conditions are exhibited under which the sequence constructed from cumulative class frequencies by linear interpolation with respect to the class boundaries converges to a Gaussian process in law when the support of latent distribution is a bounded interval. We then extend the result to more general unbounded support. Quadratic variation of the limiting process is derived.

Journal ArticleDOI
Arindam Sengupta1Institutions (1)

1 citations

Journal ArticleDOI
Arindam Sengupta1Institutions (1)

1 citations

Journal ArticleDOI
01 Feb 2014
Abstract: Theorem 2.2 of Majumdar (Sankhyā 67:670–673, 2005) obtained two conditions that are necessary and jointly sufficient for weak convergence in $${\mathcal{M}}\left({H}\right)$$. In this note we significantly relax the second condition while maintaining the joint sufficiency.

1 citations

##### Cited by
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Journal ArticleDOI
Yan Feng1, Yun-Jie Wang1, Runhe Qiu1, Kun Zhang1  +3 moreInstitutions (1)
Abstract: The well-known multidimensional reconciliation is a significant stage of a continuous-variable quantum key distribution (CVQKD) system, which uses $d$-dimensional rotations to build a virtual channel between authenticated parties, Alice and Bob. Generally, a block low-density parity-check code with a belief-propagation (BP) iterative decoding algorithm, which is optimized for an additive white Gaussian noise channel, is always used in multidimensional reconciliation for the CVQKD system. In this paper, we study the signal-to-noise ratio (SNR) of the virtual channel of multidimensional reconciliation in CVQKD and prove that the noise of the virtual channel follows the Student's $t$-distribution. Therefore, we propose a $t$-BP decoding algorithm, which can be better applied to multidimensional reconciliation. Simulation results show that the frame error rate (FER) with the proposed $t$-BP decoding algorithm is superior to that with the conventional BP decoding algorithm applied to multidimensional reconciliation. Subsequently, the FER improvement results in significant influence on reconciliation efficiency and secret key rate of the CVQKD system.

1 citations

Journal ArticleDOI
Abstract: Asymptotic tests for identical distribution of responses in two independent sets of Likert-type scale data using latent variable models are developed. The proposed tests are compared with regard to...

Journal ArticleDOI
TL;DR: A low-cost multispectral imager was built using a multiwavelength LED PCB, 3D printed housing, and a monochrome camera, and it was controlled via Nation.
Abstract: A low-cost multispectral imager was built using a multiwavelength LED PCB (light-emitting diode printed circuit board), 3D printed housing, and a monochrome camera, and it was controlled via Nation...

2 citations

Posted Content
Abstract: In the last ten years, the employment of symbolic methods has substantially extended both the theory and the applications of statistics and probability. This survey reviews the development of a symbolic technique arising from classical umbral calculus, as introduced by Rota and Taylor in $1994.$ The usefulness of this symbolic technique is twofold. The first is to show how new algebraic identities drive in discovering insights among topics apparently very far from each other and related to probability and statistics. One of the main tools is a formal generalization of the convolution of identical probability distributions, which allows us to employ compound Poisson random variables in various topics that are only somewhat interrelated. Having got a different and deeper viewpoint, the second goal is to show how to set up algorithmic processes performing efficiently algebraic calculations. In particular, the challenge of finding these symbolic procedures should lead to a new method, and it poses new problems involving both computational and conceptual issues. Evidence of efficiency in applying this symbolic method will be shown within statistical inference, parameter estimation, Levy processes, and, more generally, problems involving multivariate functions. The symbolic representation of Sheffer polynomial sequences allows us to carry out a unifying theory of classical, Boolean and free cumulants. Recent connections within random matrices have extended the applications of the symbolic method.

11 citations

Journal ArticleDOI
Abstract: We prove that under certain conditions the excursion sets volumes of stationary positively associated random fields converge after rescaling to the normal distribution as the excursion level and the size of the observation window grow In addition, we provide a number of examples

3 citations

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Author's H-index: 5

No. of papers from the Author in previous years
YearPapers
20211
20171
20151
20142
20131
20111