The random projection method in goodness of fit for functional data
From MaRDI portal
Publication:1020143
DOI10.1016/j.csda.2006.09.007zbMath1162.62363OpenAlexW2118643621MaRDI QIDQ1020143
Eustasio del Barrio, Carlos Matrán, Juan Antonio Cuesta-Albertos, Ricardo Fraiman
Publication date: 29 May 2009
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10908/505
stochastic processesgoodness-of-fit testsGaussian distributionsBlack-Scholesrandom projectionsfamilies of distributions
Nonparametric hypothesis testing (62G10) Point estimation (62F10) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Applications of functional analysis in probability theory and statistics (46N30)
Related Items
A random-projection based test of Gaussianity for stationary processes, SPECIFICATION TEST FOR MISSING FUNCTIONAL DATA, An ensemble learning method for variable selection: application to high-dimensional data and missing values, Unnamed Item, A consistent goodness-of-fit test for huge dimensional and functional data, Different perspectives on object oriented data analysis, An updated review of goodness-of-fit tests for regression models, A partial overview of the theory of statistics with functional data, Modeling functional data: a test procedure, A one-sample test for normality with kernel methods, A simple multiway ANOVA for functional data, Classifying Speech Sonority Functional Data using a Projected Kolmogorov–Smirnov Approach, A non-Gaussian multivariate distribution with all lower-dimensional Gaussians and related families, Letter to the editor, Multivariate analysis of variance for functional data, Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes, Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data, The Tukey and the random Tukey depths characterize discrete distributions, Projection pursuit based tests of normality with functional data, On depth measures and dual statistics. A methodology for dealing with general data, Testing the equality of a large number of means of functional data, Statistics for functional data, Bayesian random projection-based signal detection for Gaussian scale space random fields, Change-Point Detection of the Mean Vector with Fewer Observations than the Dimension Using Instantaneous Normal Random Projections, Goodness-of-fit tests for functional data, High-dimensional outlier detection using random projections, Testing marginal homogeneity in Hilbert spaces with applications to stock market returns, A review of goodness-of-fit tests for models involving functional data, Random projections and Hotelling’s T2 statistics for change detection in high-dimensional data streams
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A spectral algorithm for learning mixture models
- A new test for multivariate normality
- Random projections and goodness-of-fit tests in infinite-dimensional spaces
- Approximations of the empirical process when parameters are estimated
- Stochastic calculus for finance. II: Continuous-time models.
- Weak convergence and empirical processes. With applications to statistics
- Asymptotics of graphical projection pursuit
- Weak convergence of the sample distribution function when parameters are estimated
- A sharp form of the Cramér-Wold theorem
