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Titlebook: Applied Statistical Methods; ISGES 2020, Pune, In David D. Hanagal,Raosaheb V. Latpate,Girish Chandr Conference proceedings 2022 The Editor

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,Probabilistic Supply Chain Models with?Partial Backlogging for?Deteriorating Items,and rate, an inventory can be optimized. Here, we develop the inventory models by assuming various probability distributions for demand and deterioration rate under shortages. For modeling, we consider probabilistic demand per unit time as well as the probabilistic deterioration rates. Under these a
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發(fā)表于 2025-3-25 16:40:52 | 只看該作者
The Evolution of Dynamic Gaussian Process Model with Applications to Malaria Vaccine Coverage Predicountries concentrated in the tropical belt. In 2019 alone, it was the cause of more than 435,000 deaths worldwide. The malice is easy to cure if diagnosed in time, but the common symptoms make it difficult. We focus on a recently discovered reliable vaccine called Mosquirix (RTS,S) which is current
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發(fā)表于 2025-3-25 20:12:31 | 只看該作者
Grey Relational Analysis for the Selection of Potential Isolates of , of Poplar,etter attributes were the choice for isolate selection in GRA. For choosing top fifteen isolates, equal and variable weights to all the four attributes were used. Distinguishing coefficients of 0.1–0.9 with step-up size 0.2 were taken for the analysis. GRA normalizes the measured values of all attri
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發(fā)表于 2025-3-26 03:05:38 | 只看該作者
A Bayesian Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent Randomization M imbalanced covariates are associated with the outcome of interest, particularly with small to moderate sample sizes. To combine the advantages of Q-learning-decision-consistent strategies and response-adaptive designs while controlling for covariate balance, we propose a Bayesian response-adaptive,
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Roger N. Walsh,Robert A. Cumminss areas. We provide efficient Gibbs samplers to make inference about the cell probabilities for multinomial Dirichlet models with and without order restrictions (a model with the same pooling structure). To make inference, we compute the posterior distributions of the cell probabilities for both mod
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