Results 121 to 130 of about 17,400 (155)
Pharmacoepidemiology and Drug Safety, 2016 AbstractBackgroundWastewater‐based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential ...
Stefania, Salvatore +3 more
openaire +3 more sources
, 2014 RNA-seq, next-generation sequencing (NGS) applied to RNA, is rapidly becoming the platform of choice for gene expression profiling. Existing methods, mostly parametric, describe the expression level of a gene or transcript by a single number that summarizes all reads mapped to that gene or transcript.
Hao Xiong +4 more
openaire +2 more sources
A Multi-Dimensional Functional Principal Components Analysis of EEG Data
Biometrics, 2017 Kyle Hasenstab +2 more
exaly +2 more sources
Covariate adjusted functional principal components analysis for longitudinal data [PDF]
Annals of Statistics, 2010 Classical multivariate principal component analysis has been extended to functional data and termed functional principal component analysis (FPCA). Most existing FPCA approaches do not accommodate covariate information, and it is the goal of this paper
Ci-Ren Jiang, Jane-Ling Wang
exaly +2 more sources
Conditional Functional Principal Components Analysis
Scandinavian Journal of Statistics, 2007 Herve Cardot
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Evaluating variability in foot to pedal movements using functional principal components analysis
Accident Analysis and Prevention, 2018There are reasons why the driver's foot may not be applied to the correct pedal while driving and this can lead to unintended consequences. In this study, we seek to capture common and unique patterns of variations in drivers' foot movements using ...
Linda Ng Boyle, Daniel V Mcgehee
exaly +2 more sources
Robust Bayesian functional principal component analysis
Statistics and computing, 2023We develop a robust Bayesian functional principal component analysis (RB-FPCA) method that utilizes the skew elliptical class of distributions to model functional data, which are observed over a continuous domain.
Jiarui Zhang, Jiguo Cao, Liangliang Wang
semanticscholar +1 more source
Journal of Applied Meteorology and Climatology, 2023
We propose a statistical downscaling model based on multi-way functional principal component analysis (FPCA) for rainfall prediction. The model mainly explains the relationship between the winter mean sea level pressure (MSLP) and rainfall in southern ...
Shuren Cao +3 more
semanticscholar +1 more source
We propose a statistical downscaling model based on multi-way functional principal component analysis (FPCA) for rainfall prediction. The model mainly explains the relationship between the winter mean sea level pressure (MSLP) and rainfall in southern ...
Shuren Cao +3 more
semanticscholar +1 more source
2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 2022
The monitoring of cropland areas and in particular the capability to evaluate the performance of a field over space and time is becoming a crucial activity to schedule agronomic operations (e.g., fertilization) properly.
L. Coviello +5 more
semanticscholar +1 more source
The monitoring of cropland areas and in particular the capability to evaluate the performance of a field over space and time is becoming a crucial activity to schedule agronomic operations (e.g., fertilization) properly.
L. Coviello +5 more
semanticscholar +1 more source
Robust functional principal components for sparse longitudinal data
Metron, 2020In this paper we review existing methods for robust functional principal component analysis (FPCA) and propose a new method for FPCA that can be applied to longitudinal data where only a few observations per trajectory are available.
G. Boente, M. Salibián‐Barrera
semanticscholar +1 more source