论文部分内容阅读
Functional data vectors consist of samples of multivariate data in which each component is a random function.
Modeling dependent functional data
【摘 要】
：
Functional data vectors consist of samples of multivariate data in which each component is a random function.
【机 构】
：
Academia Sinica,11529,Taipei University of Califo
【出 处】
：
上海交通大学
【发表日期】
：
2016年4期
其他文献
Dynamic prediction is an important statistical tool for aiding medical decision-making,such as early detection of disease onset,post-treatment monitoring of disease prognosis.For this purpose,subjects
Let T = {T(x),x∈ 2 S2} be a Gaussian random field with values in Rd defined by T(x)=(T1(x),……,Td(x)),x ∈2 S2; where T1,……,Td are independent copies of a real-valued,centered,isotropic Gaussian random
Hidden Markov models is an important statistical method in exploring the possible heterogeneity of data and explaining the pattern of subjects moving from one group to another over time.
Modern statistical applications increasingly require the fitting of complex statistical models the likelihood of which are often difficult to be evaluated.
The term structure of interest rates,also called the yield curve,describes how the interest rate of bonds evolves over time,which is a central concept in economic and financial theory.
Screening designs are designs conducted at the primary stage of the experiment to screen out significant factors from a large number of factors for further studies.
For clinical genomic studies with high-dimensional datasets,tree-based ensemble methods offer a powerful solution for variable selection and prediction taking into account the complex interrelationshi
Large-scale predictive modeling tasks routinely emerge in various fields.In many realworld problems,the collected outcomes are of mixed types,including continuous measurements,binary indicators and co
We investigate properties of node centrality in random growing tree models.We focus on a measure of centrality that computes the maximum subtree size of the tree rooted at each node,with the most cent