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Category Archives: Communications in Statistics – Simulation and Computation
A dynamic approach to relative taxonomy and robust measures of central tendency
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Alternative methods for interpreting Monte Carlo experiments
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Bayesian framework for interval-valued data using Jeffreys’ prior and posterior predictive checking methods
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Mitigating lack of trust in quantitative randomized response technique models
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Correction to: Jayakumar, K., & Sankaran, K. K. (2019). Discrete Linnik Weibull distribution. Communications in Statistics—Simulation and Computation, 48 (10): 3092–117
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GMM-based procedure for multiple hypotheses testing
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The evaluation of the p-value as an estimator for the null hypothesis in the exponential distribution
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Bayesian estimation for geometric process with the Weibull distribution
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Asymptotic normality of error distribution estimator in autoregressive models
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