BILK
发表于 2025-3-23 11:03:14
Jaitri Das,Buddhadeb Chattopadhyayn models for longitudinal data, focusing on continuous-time (CT) models. Unlike the more widely used discrete-time (DT) models, CT models do not require the time intervals between measurements to be equal and, therefore, can adapt effortlessly to irregular sampling schemes. Thus, our resulting appro
令人作呕
发表于 2025-3-23 17:38:47
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生锈
发表于 2025-3-23 20:43:53
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尊敬
发表于 2025-3-23 23:28:05
Mauro Ferrario,Maria Clelia Righiearly related to each other, and errors may be multiplicative. Thus, the present chapter discusses linearizable non-linear models for which distributional and independence-based direction dependence measures are applicable. Simulation results suggest that direction of dependence properties of linear
Visual-Field
发表于 2025-3-24 03:34:23
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botany
发表于 2025-3-24 10:07:18
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ATOPY
发表于 2025-3-24 13:39:30
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取消
发表于 2025-3-24 16:52:05
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CROW
发表于 2025-3-24 20:28:56
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PACK
发表于 2025-3-24 23:14:39
Engineered Fe-Based Nanocolumnar Films,n the construction of analytical models. In this chapter, we look at how longitudinal data are analyzed in latent growth curve models. We focus on the real-world problem of sampling-time variation, when individuals do not have exactly equal intervals between measurements, its consequences, and how t