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Using Functional Data Analysis for investigating multidimensional dynamic phonetic contrasts
Functional Data Analysis Cue Trading
2015/12/18
The study of phonetic contrasts and related phenomena, e.g. inter- and intra-speaker variability, often requires to
analyse data in the form of measured time series, like f0 contours and formant traj...
Principal component models for sparse functional data
Functional data analysis Principal components Mixed effects model Reduced rank estimation Growth curve
2015/8/21
The elements of a multivariate data set are often curves rather than single points. Functional principal components can be used to describe the modes of variation of such curves. If one has complete m...
Using Functional Data Analysis for investigating multidimensional dynamic phonetic contrasts
Functional Data Analysis Cue Trading Dynamic trajectories Diphthong and hiatus European Spanish
2015/5/13
he study of phonetic contrasts and related phenomena, e.g. inter- and intra-speaker variability, often requires to analyse data in the form of measured time series, like f0 contours and formant trajec...
Spatial Depth-Based Classification for Functional Data
Functional depths Functional outliers Spatial functional depth Supervised func-tional classification
2013/6/14
We enlarge the available number of functional depths by defining two new depth measures for curves. Both depths are based on a spatial approach: the functional spatial depth (FSD), that shows an inter...
TEXT-DEPENDENT SPEAKER RECOGNIT ION WITH LONG-TERM FEATURES BASED ON FUNCTIONAL DATA ANALYSIS
Text-dependent speaker recognition functional data analysis functional principle component analysis distance metrics
2013/6/28
Text-Dependent Speaker Recognition (TDSR) is widely used nowadays. The short-term features like Mel-Frequency Cepstral Coefficient (MFCC) have been the dominant features used in traditional...
Variance estimation and asymptotic confidence bands for the mean estimator of sampled functional data with high entropy unequal probability sampling designs
covariance function finite population Hajek approximation Horvitz-Thompso estimator Kullback-Leibler divergence rejective sampling unequal probability sampling without replacement
2012/11/23
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the H\'ajek formula. The interest of this asymptotic varia...
Ancestral Inference from Functional Data: Statistical Methods and Numerical Examples
comparative analysis Ornstein-Uhlenbeck process non-parametric Bayesian infer-ence functional phylogenetics ancestral reoncon-struction
2012/9/17
Many biological characteristics of evolutionary inter-est are not scalar variables but continuous functions.Here we use phylogenetic Gaussian process regres-sion to model the evolution of simulated fu...
General notions of depth for functional data
Multivariate functional depth central regions trimmed regions -depth graph depth location-slope depth grid depth principal component depth
2012/9/17
A data depth measures the centrality of a point with respect to an empirical distribution. Postulates are formulated, which a depth for functional data should satisfy, and a general approach is propos...
Local Polynomial Regression Based on Functional Data
Local polynomial smoothing derivative estimation functional data sampling density optimal bandwidth asymptotic normality
2011/9/15
Abstract: Suppose that $n$ statistical units are observed, each following the model $Y(x_j)=m(x_j)+ \epsilon(x_j),\, j=1,...,N,$ where $m$ is a regression function, $0 \leq x_1 <...N \leq 1$ are ob...
Revealing spatial variability structures of geostatistical functional data via Dynamic Clustering
functional data clustering geostatistics variogram
2011/7/6
In several environmental applications data are functions of time, essentially con- tinuous, observed and recorded discretely, and spatially correlated. Most of the methods for analyzing such data are ...
Resistant estimates for high dimensional and functional data based on random projections
Resistant estimates high dimensional functional data based
2011/7/5
In this paper we propose a new robust estimation method based on random projections which is adaptive, produces an automatic robust estimate, while being easy to compute for high or infinite dimension...
Confidence bands for Horvitz-Thompson estimators using sampled noisy functional data
CLT functional data local polynomial smoothing maximal inequalities space of continuous functions suprema of Gaussian processes survey sampling weighted crossvalidation
2011/6/17
When collections of functional data are too large to be exhaustively observed, survey
sampling techniques provide an e ective way to estimate global quantities such as
the population mean function. ...
Semi-supervised logistic discrimination for functional data
EM algorithm Functional data analysis Model selec-tion Regularization Semi-supervised learning
2011/3/24
Multi-class classification methods based on both labeled and unlabeled functional data sets are discussed. We present semi-supervised logistic models for classification in the context of functional da...
A Hierarchical Model for Aggregated Functional Data
Bayes'theorem B-splines Covariance function Gaussian process
2011/3/21
In many areas of science one aims to estimate latent sub-population mean curves based only on observations of aggregated population curves. By aggregated curves we mean linear combination of functiona...
Functional data often arise from measurements on fine time grids and are obtained by separating an almost continuous time record into natural consecutive intervals, for example, days. The functions th...