Functional data analysis
Contributions to Statistical Methods for Functional Data Analysis and Generalized Additive Model.
... new data acquisition and storage technologies has also created the de- mand for analyzing big datasets, which feature a large number of predictors and possibly a large number of observations as ...further ...
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Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data
... the analysis is a seven day week starting Wednesday and ending ...Missing data across all the 38 cities was ...frequentist functional data analysis (FDA) needs complete data sets ...
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Applications of functional data analysis: A systematic review
... series data, a key strength of the FDA approach is that it makes no parametric assumptions about age or time ...forecasting data across a range of health and demo- graphic issues also have significant ...
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Longitudinal Functional Data Analysis with Biomedical Applications.
... Functional Data Analysis (FDA) is an actively growing research area in Statistics that involves data with each observation being a function instead of a single ...marathon data, where ...
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Smoothing wind and rainfall data through functional data analysis technique
... Functional Data Analysis (FDA) develops fast in statistics area with the aim of estimating a set of related functions or curves rather than focusing on a single ...a functional data ...
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Functional data analysis in phonetics
... phonetic analysis that is both linguistically and experimentally coherent based on the general paradigms presented in Quantitative Linguistics for example by Baayen [16] and Johnson ...the analysis of low- ...
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Functional Data Analysis with Applications in Animal Science and Biomedical Engineering.
... Functional data analysis (FDA) technique is a statistical approach which has been exten- sively used in analyzing high dimensional data in various ...term functional refers to the ...
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Similarities within a multi-model ensemble: functional data analysis framework
... Abstract. Despite the abundance of available global climate model (GCM) and regional climate model (RCM) outputs, their use for evaluation of past and future climate change is often complicated by substantial differences ...
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Covariance-based Clustering in Multivariate and Functional Data Analysis
... collect data are described in (Torricelli et ...the data set consists of a sampling along 40 seconds of deoxygenated hemoglobin’s concentration at the related location on the ...
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Classifying Aneugens Using Functional Data Analysis Techniques
... the functional curves that originate from human TK6 cells exposed to fluorescent Taxol (Taxol 488) for four hours and co-treated with known aneugens over a range of ...large functional space of classifiers ...
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Shape information from glucose curves: Functional data analysis compared with traditional summary measures
... While a FPCA will decompose the variation between individual curves into a set of uncorrelated, temporal features, the clinical usefulness of this analysis depends on how the FPCs are interpreted. In this study, ...
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Statistical analysis of wind and rainfall with functional data analysis technique
... 4.2 Analysis Deviance of Daily Mean Wind Speed for Mersing 36 4.3 Analysis Deviance of Daily Mean Rainfall Data for Kuala Krai 36 ...Rainfall Data 37 ...
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Functional Analysis of Chemometric Data
... the data are curv- es derived from the observation of a functional ...such data which have been developed in recent years is a branch of statistics known as Functional Data ...
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Happ, Clara Maria (2017): Statistical methods for data with different dimensions: multivariate functional PCA and scalar-on-image regression. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... multivariate data to the functional case, by simply apply- ing them to the coefficient vectors and transforming the result back to the original ...component analysis (Ramsay and Silverman, 2005, ...
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High-Dimensional Linear and Functional Analysis of Multivariate Grapevine Data
... decades, data collection technology has evolved to measure observations densely sampled over time, wavelength, space and other ...of data, it is more natural to think in functional terms even though ...
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Multivariate Functional Regression for Classification With an Application to Geology
... the data observed are naturally described as dis- cretized functions or curves rather than vectors of fea- ture values ...of functional data analysis can help to overcome these prob- lems of ...
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Highway Asset Management Framework for Longevity of Infrastructure – A Case Study for China-Pakistan Economic Corridor
... and functional evaluation of all lanes of the existing pavement structure to avail the window of opportunity to extend the pavement life by another 10 years or ...pavement functional and structural ...
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Hybridisation-based target enrichment of phenology genes to dissect the genetic basis of yield and adaptation in barley
... yield data collected from field experiments was analysed using mixed linear model analysis to determine Best Linear Unbiased Predictions (BLUPs) for each trait for further ...
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Functional Mediation Analysis with an Application to Multiple Myeloma and Copy Number Variation Data.
... survival analysis, and causal mediation ...counterfactual functional mediation model with a survival ...survival data, we consider the parametric AFT model and the semi-parametric Cox model under two ...
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Estimation of functional sparsity in nonparametric varying coefficient models for longitudinal data analysis
... of functional sparsity and propose a one-step penalized estimation procedure that auto- matically determines the types of functional sparsity, being local or ...for functional sparsity its true ...
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