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搜索结果: 1-15 共查到Functional data相关记录23条 . 查询时间(0.127 秒)
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...
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...
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...
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 Recognition (TDSR) is widely used nowadays. The short-term features like Mel-Frequency Cepstral Coefficient (MFCC) have been the dominant features used in traditional...
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...
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...
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...
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...
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 ...
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...
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. ...
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       font style='font-size:12px;'> 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...
Weakly dependent functional data     Asymptotics  change points  eigenfunctions       font style='font-size:12px;'> 2010/10/15
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...

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