Now showing items 1-10 of 10
| URI: | http://dyuthi.cusat.ac.in/purl/1678 |
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| Dyuthi-T0053.pdf | (2.210Mb) |
| Abstract: | In this paper, we examine the relationships between log odds rate and various reliability measures such as hazard rate and reversed hazard rate in the context of repairable systems. We also prove characterization theorems for some families of distributions viz. Burr, Pearson and log exponential models. We discuss the properties and applications of log odds rate in weighted models. Further we extend the concept to the bivariate set up and study its properties. |
| Description: | Statistics, Vol. 41, No. 5, October 2007, 443–451 |
| URI: | http://dyuthi.cusat.ac.in/purl/4283 |
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| Characterizatio ... ns using log odds rate.pdf | (111.4Kb) |
| Abstract: | In this article, we study reliability measures such as geometric vitality function and conditional Shannon’s measures of uncertainty proposed by Ebrahimi (1996) and Sankaran and Gupta (1999), respectively, for the doubly (interval) truncated random variables. In survival analysis and reliability engineering, these measures play a significant role in studying the various characteristics of a system/component when it fails between two time points. The interrelationships among these uncertainty measures for various distributions are derived and proved characterization theorems arising out of them |
| Description: | Communications in Statistics—Theory and Methods, 38: 1441–1452, 2009 |
| URI: | http://dyuthi.cusat.ac.in/purl/4273 |
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| Characterizatio ... Expectations of Doubly.pdf | (133.5Kb) |
| Abstract: | In the present environment, industry should provide the products of high quality. Quality of products is judged by the period of time they can successfully perform their intended functions without failure. The cause of the failures can be ascertained through life testing experiments and the times to failure due to different cause are likely to follow different distributions. Knowledge of this distribution is essential to eliminate causes of failures and thereby to improve the quality and the reliability of products. The main accomplishment expected to the study is to develop statistical tools that could facilitate solution to lifetime data arising in such and similar contexts |
| URI: | http://dyuthi.cusat.ac.in/purl/1011 |
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| Dyuthi-T0111.pdf | (1.141Mb) |
| Abstract: | In this paper, we study the relationship between the failure rate and the mean residual life of doubly truncated random variables. Accordingly, we develop characterizations for exponential, Pareto 11 and beta distributions. Further, we generalize the identities for fire Pearson and the exponential family of distributions given respectively in Nair and Sankaran (1991) and Consul (1995). Applications of these measures in file context of lengthbiased models are also explored |
| Description: | Statistical Papers 45, 97-109 (2004) |
| URI: | http://dyuthi.cusat.ac.in/purl/4276 |
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| Identification ... cated random variables.pdf | (393.9Kb) |
| Abstract: | Quantile functions are efficient and equivalent alternatives to distribution functions in modeling and analysis of statistical data (see Gilchrist, 2000; Nair and Sankaran, 2009). Motivated by this, in the present paper, we introduce a quantile based Shannon entropy function. We also introduce residual entropy function in the quantile setup and study its properties. Unlike the residual entropy function due to Ebrahimi (1996), the residual quantile entropy function determines the quantile density function uniquely through a simple relationship. The measure is used to define two nonparametric classes of distributions |
| Description: | Statistics and Probability Letters 82 (2012) 1049–1053 |
| URI: | http://dyuthi.cusat.ac.in/purl/4280 |
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| Quantile based entropy function.pdf | (207.9Kb) |
| Abstract: | Di Crescenzo and Longobardi (2002) introduced a measure of uncertainty in past lifetime distributions and studied its relationship with residual entropy function. In the present paper, we introduce a quantile version of the entropy function in past lifetime and study its properties. Unlike the measure of uncertainty given in Di Crescenzo and Longobardi (2002) the proposed measure uniquely determines the underlying probability distribution. The measure is used to study two nonparametric classes of distributions. We prove characterizations theorems for some well known quantile lifetime distributions |
| Description: | Statistics and Probability Letters 83 (2013) 366–372 |
| URI: | http://dyuthi.cusat.ac.in/purl/4284 |
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| Quantile based ... ction in past lifetime.pdf | (227.4Kb) |
| Abstract: | Partial moments are extensively used in literature for modeling and analysis of lifetime data. In this paper, we study properties of partial moments using quantile functions. The quantile based measure determines the underlying distribution uniquely. We then characterize certain lifetime quantile function models. The proposed measure provides alternate definitions for ageing criteria. Finally, we explore the utility of the measure to compare the characteristics of two lifetime distributions |
| Description: | Journal of the Korean Statistical Society 42 (2013) 329–342 |
| URI: | http://dyuthi.cusat.ac.in/purl/4289 |
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| Quantile based ... cts of partial moments.pdf | (253.9Kb) |
| Abstract: | Partial moments are extensively used in actuarial science for the analysis of risks. Since the first order partial moments provide the expected loss in a stop-loss treaty with infinite cover as a function of priority, it is referred as the stop-loss transform. In the present work, we discuss distributional and geometric properties of the first and second order partial moments defined in terms of quantile function. Relationships of the scaled stop-loss transform curve with the Lorenz, Gini, Bonferroni and Leinkuhler curves are developed |
| Description: | Stat Methods Appl (2013) 22:167–182 DOI 10.1007/s10260-012-0213-4 |
| URI: | http://dyuthi.cusat.ac.in/purl/4290 |
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| Quantile based ... m and its applications.pdf | (183.4Kb) |
| Abstract: | In the present paper, we introduce a quantile based Rényi’s entropy function and its residual version. We study certain properties and applications of the measure. Unlike the residual Rényi’s entropy function, the quantile version uniquely determines the distribution |
| Description: | Statistics and Probability Letters 85 (2014) 114–121 |
| URI: | http://dyuthi.cusat.ac.in/purl/4288 |
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| Rényi’s residual entropy A quantile approach.pdf | (378.5Kb) |
Now showing items 1-10 of 10
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