Results 31 to 40 of about 33,054,453 (365)

Bayesian Nonparametric Mixture Estimation for Time-Indexed Functional Data in R

Journal of Statistical Software, 2016
We present growfunctions for R that offers Bayesian nonparametric estimation models for analysis of dependent, noisy time series data indexed by a collection of domains.
Terrance D. Savitsky
doaj   +1 more source

Structural components in functional data. [PDF]

, 2009
Analyzing functional data often leads to finding common factors, for which functional principal component analysis proves to be a useful tool to summarize and characterize the random variation in a function space.
Gasser, T, Theo Gasser, Juhyun Park, Gasser, Theo, Rousson, Valentin, Park, J, Park, Juhyun, Valentin Rousson, Rousson, V   +8 more
core   +1 more source

The Impact of Sovereign Yield Curve Differentials on Value-at-Risk Forecasts for Foreign Exchange Rates

Risks, 2018
A functional ARMA-GARCH model for predicting the value-at-risk of the EURUSD exchange rate is introduced. The model implements the yield curve differentials between EUR and the US as exogenous factors. Functional principal component analysis allows us to
Holger Fink, Andreas Fuest, Henry Port
doaj   +1 more source

Categorical Functional Data Analysis. The cfda R Package

Mathematics, 2021
Categorical functional data represented by paths of a stochastic jump process with continuous time and a finite set of states are considered. As an extension of the multiple correspondence analysis to an infinite set of variables, optimal encodings of ...
Cristian Preda, Quentin Grimonprez, Vincent Vandewalle   +2 more
doaj   +1 more source

Longitudinal functional data analysis [PDF]

Stat, 2015
We consider dependent functional data that are correlated because of a longitudinal‐based design: each subject is observed at repeated times and at each time, a functional observation (curve) is recorded. We propose a novel parsimonious modelling framework for repeatedly observed functional observations that allows to extract low‐dimensional features ...
Park, So Young, Staicu, Ana-Maria
openaire   +3 more sources

Curve Registration of Functional Data for Approximate Bayesian Computation

Stats, 2021
Approximate Bayesian computation is a likelihood-free inference method which relies on comparing model realisations to observed data with informative distance measures.
Anthony Ebert, Kerrie Mengersen, Fabrizio Ruggeri, Paul Wu   +3 more
doaj   +1 more source

Copula Gaussian Graphical Models for Functional Data

Journal of the American Statistical Association, 2020
We introduce a statistical graphical model for multivariate functional data, which are common in medical applications such as EEG and fMRI. Recently published functional graphical models rely on the multivariate Gaussian process assumption, but we relax ...
Eftychia Solea, Bing Li
semanticscholar   +1 more source

Pattern Functional Dependencies for Data Cleaning [PDF]

, 2020
Patterns (or regex-based expressions) are widely used to constrain the format of a domain (or a column), e.g., a Year column should contain only four digits, and thus a value like “1980-” might be a typo.
Stonebraker, Michael, Sub Data Intensive Systems, Qahtan, A.A.A., Tang, Nan, Cao, Yang; id_orcid, Ouzzani, Mourad, Cao, Yang, Qahtan, Abdulhakim, Data Intensive Systems   +8 more
core   +1 more source

Clonal tracing reveals diverse patterns of response to immune checkpoint blockade

Genome Biology, 2020
Background Immune checkpoint blockade (ICB) therapy has improved patient survival in a variety of cancers, but only a minority of cancer patients respond.
Shengqing Stan Gu, Xiaoqing Wang, Xihao Hu, Peng Jiang, Ziyi Li, Nicole Traugh, Xia Bu, Qin Tang, Chenfei Wang, Zexian Zeng, Jingxin Fu, Cliff Meyer, Yi Zhang, Paloma Cejas, Klothilda Lim, Jin Wang, Wubing Zhang, Collin Tokheim, Avinash Das Sahu, Xiaofang Xing, Benjamin Kroger, Zhangyi Ouyang, Henry Long, Gordon J. Freeman, Myles Brown, X. Shirley Liu   +25 more
doaj   +1 more source

Dependent Functional Data [PDF]

ISRN Probability and Statistics, 2012
This paper reviews recent research on dependent functional data. After providing an introduction to functional data analysis, we focus on two types of dependent functional data structures: time series of curves and spatially distributed curves. We review statistical models, inferential methodology, and possible extensions.
openaire   +1 more source