Results 111 to 120 of about 17,164 (153)
Some of the next articles are maybe not open access.
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 +2 more sources
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 +2 more sources
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 ...
Yuqing Wu, L. Boyle, D. McGehee
semanticscholar +1 more source
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
Fast Bayesian Functional Principal Components Analysis
Journal of Computational And Graphical StatisticsFunctional Principal Components Analysis (FPCA) is a widely used analytic tool for dimension reduction of functional data. Traditional implementations of FPCA estimate the principal components from the data, then treat these estimates as fixed in ...
Joseph Sartini +4 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
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 +1 more source
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 +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
Filtrated common functional principal component analysis of multigroup functional data
Annals of Applied StatisticsLocal field potentials (LFPs) are signals that measure electrical activities in localized cortical regions and are collected from multiple tetrodes implanted across a patch on the surface of cortex. Hence, they can be treated as multigroup functional data,
Shuhao Jiao, Ron D. Frostig, H. Ombao
semanticscholar +1 more source
Statistics in Medicine
In studying the association between clinical measurements and time‐to‐event outcomes within a cure model, utilizing repeated observations rather than solely baseline values may lead to more accurate estimation.
Siyuan Guo, Jiajia Zhang, S. Halabi
semanticscholar +1 more source
In studying the association between clinical measurements and time‐to‐event outcomes within a cure model, utilizing repeated observations rather than solely baseline values may lead to more accurate estimation.
Siyuan Guo, Jiajia Zhang, S. Halabi
semanticscholar +1 more source