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文献信息
The Journal of the Indian Society for Probability and Statistics is dedicated to advancing research in probability, statistics, and their applications across various fields of science and technology. The journal provides a platform for original theoretical and applied contributions that deepen understanding of probabilistic models, statistical methodologies, and data-driven insights relevant to both regional and global contexts.
Probability and StatisticsIndian SocietyMaximum Likelihood EstimationMaximum LikelihoodMonte Carlo SimulationRandom VariablesMoment Generating FunctionBayesian EstimationOrder StatisticsMaximum Likelihood EstimatorQuantile FunctionExponential DistributionSquared Error Loss FunctionWEIBULL DistributionPROPOSED MODELMaximum Likelihood MethodMean Square ErrorPareto DistributionCensored DataLindley Distribution
vol.26 (2025)
vol.25 (2024)
vol.24 (2023)
vol.23 (2022)
vol.22 (2021)
vol.21 (2020)
vol.20 (2019)
Astafiev, SergeyMorozov, EvseyRumyantsev, Alexander