Covariance Partition Priors: A Bayesian Approach to Simultaneous Covariance Estimation for Longitudinal Data
نویسندگان
چکیده
منابع مشابه
A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data.
Estimation of the covariance structure for irregular sparse longitudinal data has been studied by many authors in recent years but typically using fully parametric specifications. In addition, when data are collected from several groups over time, it is known that assuming the same or completely different covariance matrices over groups can lead to loss of efficiency and/or bias. Nonparametric ...
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In the modeling of longitudinal data from several groups, appropriate handling of the dependence structure is of central importance. Standard methods include specifying a single covariance matrix for all groups or independently estimating the covariance matrix for each group without regard to the others, but when these model assumptions are incorrect, these techniques can lead to biased mean ef...
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هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...
15 صفحه اولNonparametric Covariance Function Estimation for Functional and Longitudinal Data
Covariance function plays a critical role in functional and longitudinal data analysis. In this paper, we consider nonparametric covariance function estimation using a reproducing kernel Hilbert space framework. A regularization method is introduced through a careful characterization of the function space in which a covariance function resides. It is shown that the procedure enjoys desirable th...
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ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2016
ISSN: 1061-8600,1537-2715
DOI: 10.1080/10618600.2015.1028549