绊住
发表于 2025-3-30 10:37:30
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arrogant
发表于 2025-3-30 13:39:30
2194-1009 overnment, and industry-related topics.Includes contribution.This volume presents an eclectic mix of original research articles in areas covering the analysis of ordered data, stochastic modeling and biostatistics. These areas were featured in a conference held at the University of Texas at Dallas f
preservative
发表于 2025-3-30 19:36:30
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chisel
发表于 2025-3-30 22:53:52
Approximate Bayesian Estimation for Multivariate Count Time Series Modelsing using the R package INLA (r-inla.org). We illustrate it by modeling the monthly prescription counts by physicians of a focal drug from a multinational pharmaceutical firm along with monthly counts of other drugs with a sizable market share for the same therapeutic category.
勉励
发表于 2025-3-31 02:04:49
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abstemious
发表于 2025-3-31 05:45:33
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thrombus
发表于 2025-3-31 11:24:30
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首创精神
发表于 2025-3-31 14:54:00
Nonparametric Confidence Regions for ,-Momentsical results is an .-moment ratio diagram on which confidence regions for sample .-moment statistics are plotted. This gives an immediate visual indication of whether different samples can be regarded as having been drawn from the same distribution, and of which distributions are appropriate for fitting to a given data sample.
Insensate
发表于 2025-3-31 20:57:37
On Conditional Moments of Progressively Censored Order Statistics with a Time Constraintll be useful for the development of estimation methods such as the least squares estimation, best linear unbiased estimation and approximate maximum likelihood estimation methods and for deriving asymptotic distributions of the estimates of model parameters for Type-I hybrid progressively censored data.
engagement
发表于 2025-4-1 00:12:09
Estimation in a Model of Sequential Order Statistics with Ordered Hazard Ratesrates of the SOSs. These factors are the parameters of interest. Estimation of the parameters is considered by means of maximum likelihood under order restriction, by means of link functions, and in a Bayesian set-up with an order statistics prior.