论文部分内容阅读
Tree-based models provide a flexible framework for estimating the underlying regression function.
Tree-based Censoring Imputation for Personalized Medicine
【摘 要】
：
Tree-based models provide a flexible framework for estimating the underlying regression function.
【机 构】
：
University of North Carolina at Chapel Hill,27514,U.S.A.
【出 处】
：
上海交通大学
【发表日期】
：
2016年4期
其他文献
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
Functional data vectors consist of samples of multivariate data in which each component is a random function.
Optimal Fingerprinting in Detection and Attribution of Changes in Climate Extremes with Combined Sco
Detection and attribution in climate science aims to determine whether certain aspect of climate has changed over time and subsequently attribute the change to causes such as human activities.
We consider the problem of approximating the number of customers in the steady state of a queuing system by the stationary distribution of a diffusion process.
We extend the traditional worst-case,minimax analysis of stochastic convex optimization by introducing a localized form of minimax complexity for individual functions.
For general multivariate continuous-time diffusion models,we construct the asymptotic distribution of the maximum likelihood estimator(MLE)when the sample is discretely observed.
Nonparametric statistical tools for genome-wide detection of clustering and spatial association amon
Mutation signatures and landscapes in cancer genomes are the subject of intense research focus given recent reports of mutation clustering.
A computationally extremely fast algorithm designed for genomewide association studies and different
In many genomewide association studies(GWAs)and differential expression(DE)analysis studies,the outcome of interest is a multi-category phenotype.
Preprocessing data is an important step before any data analysis.In this thesis,we focus on one particular aspect,namely scaling or normalization.