115 research outputs found

    A generalization of zero-truncated Poisson-Sujatha distribution

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    A quasi Poisson-Aradhana distribution

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    In this study, a QPAD (quasi Poisson-Aradhana distribution) by compounding a PD (Poisson distribution) with a QAD (quasi Aradhana distribution) is proposed that includes PAD (Poisson-Aradhana distribution) as a particular case. Expressions for its coefficient of variation, coefficient of skewness, coefficient of kurtosis, and index of dispersion are provided and their behaviours are studied for varying values of the parameters. The QPAD is shown to be unimodal and always over-dispersed. The estimation of its parameters using the method of maximum likelihood is discussed. Finally, the goodness of fit of the QPAD is assessed for two real count datasets from ecology and the fit is compared with that of the PD, PLD (Poisson-Lindley distribution), and PAD

    A Size-Biased Poisson-Aradhana Distribution with Applications

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    In this present paper, a size-biased Poisson-Aradhana distribution (SBPAD) has been proposed and its nature has been studied graphically. Its moments and moments based measures including coefficients of variation, skewness, kurtosis and index of dispersion have been obtained and their natures have been discussed graphically. The unimodality and increasing hazard rate function of the distribution has been discussed. Method of moments and the method of maximum likelihood have been discussed for estimating the parameter. Applications of SBPAD have been explained through three examples and it gives much better fit over size-biased Poisson distribution (SBPD) and size-biased Poisson-Lindley distribution (SBPLD)

    SUJATHA DISTRIBUTION AND ITS APPLICATIONS

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    Dalit Women in History: Struggles, Voices, and Counterpublics

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    History is a projection of realities from the historian\u27s lens and parameters. The popularity and acceptance of historical accounts depend much on hegemonic structures and knowledge. The Dalit community was marginalized within the Indian economic, social, and political historiography. Gradually, with the rise of Dalit consciousness, men—the better-positioned gender of the community—tried to express their vulnerabilities from a masculinist perspective. The literature written also projected women only as extensions of male protagonists. Though the traumas Dalit women have faced due to intersectional realities are separate from that of men, they could not find a place in early literature as complete entities, entitled to be acknowledged as such. The trade union movements also sidelined the issues of Dalit women laborers. To date, issues of Dalit women\u27s property rights, longevity, education, and empowerment are largely androcentric, as the state’s schemes and policies are majorly heteronormative and male-centric. The reason why we need to keep invoking the past and history is to assert that the present condition of Dalit women has its roots in the past and their issues and voices continue to remain on the margins despite the rich social experiences they carry and represent

    A Generalized Poisson-Akash Distribution:Properties and Applications

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    A generalized Poisson- Akash distribution which includes Poisson-Akash distribution has been proposed. Its factorial moments, raw moments and central moments have been derived and studied. Some statistical properties including generating functions, hazard rate function and unimodality have been discussed. Method of moments and the method of maximum likelihood have been discussed for estimating parameters of the distribution. Applications of the proposed distribution have been explained through two count datasets and compared with other discrete distributions

    A Two-Parameter Poisson-Akash Distribution with Properties and Applications

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    This paper proposes a two-parameter Poisson- Akash distribution which includes Poisson-Akash distribution as a special case. Its moments and moments based measures have been derived and studied. Statistical properties including hazard rate function, unimodality and generating functions have been discussed. Method of moments and the method of maximum likelihood have been discussed for estimating the parameters of the distribution. Finally, applications of the proposed distribution have been explained through two count datasets from biological sciences and compared with other discrete distributions
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