Estimation and inference for dependence in multivariate data
نویسندگان
چکیده
منابع مشابه
Multivariate dependence and genetic networks inference.
A critical task in systems biology is the identification of genes that interact to control cellular processes by transcriptional activation of a set of target genes. Many methods have been developed that use statistical correlations in high-throughput data sets to infer such interactions. However, cellular pathways are highly cooperative, often requiring the joint effect of many molecules. Few ...
متن کاملModelling, Estimation and Visualization of Multivariate Dependence for High-frequency Data
Dependence modelling and estimation is a key issue in the assessment of financial risk. It is common knowledge meanwhile that the multivariate normal model with linear correlation as its natural dependence measure is by no means an ideal model. We suggest a large class of models and a dependence function, which allows us to capture the complete extreme dependence structure of a portfolio. We al...
متن کاملInformation theory, multivariate dependence, and genetic network inference
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of information theoretic quantities from data uncovers dependencies even in undersampled regimes when the joint probability distribution cannot be reliably estimated. The method is tested on synthetic data. We anticipate it...
متن کاملDependence Structures for Multivariate High–Frequency Data in Finance
Stylised facts for univariate high–frequency data in finance are well–known. They include scaling behaviour, volatility clustering, heavy tails, and seasonalities. The multivariate problem, however, has scarcely been addressed up to now. In this paper, bivariate series of high–frequency FX spot data for major FX markets are investigated. First, as an indispensable prerequisite for further analy...
متن کاملQuantile Inference with Multivariate Failure Time Data
Quantiles, especially the medians, of survival times are often used as summary statistics to compare the survival experiences between different groups. Quantiles are robust against outliers and preferred over the mean. Multivariate failure time data often arise in biomedical research. For example, in clinical trials, each patient in the study may experience multiple events which may be of the s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2010
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2009.11.005