Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Frits H. Ruymgaart"'
Autor:
Frits H. Ruymgaart, GP Lakraj
Publikováno v:
Journal of Multivariate Analysis. 155:122-132
Unlike classical principal component analysis (PCA) for multivariate data, one needs to smooth or regularize when estimating functional principal components. Silverman's method for smoothed functional principal components has nice theoretical and pra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfde9aed8633e377943c5f3384439743
https://doi.org/10.1016/j.jmva.2016.12.004
https://doi.org/10.1016/j.jmva.2016.12.004
Publikováno v:
Journal of Theoretical Probability. 27:1112-1123
The problem of a random Hermitian perturbation of a multiple isolated eigenvalue of a Hermitian operator is considered. It is shown that the combined multiplicities of the perturbed eigenvalues converge in probability to the multiplicity of the eigen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89c172e5ec59c6fdf9640432fdfe9ad4
https://doi.org/10.1007/s10959-013-0482-3
https://doi.org/10.1007/s10959-013-0482-3
Autor:
Frits H. Ruymgaart, R. M. Mnatsakanov
Publikováno v:
Statistics. 46:215-230
An unknown moment-determinate cumulative distribution function or its density function can be recovered from corresponding moments and estimated from the empirical moments. This method of estimating an unknown density is natural in certain inverse es
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef7111ee74767e1610d47108d7247835
https://doi.org/10.1080/02331888.2010.506277
https://doi.org/10.1080/02331888.2010.506277
Autor:
Johnny Pang, Frits H. Ruymgaart
Publikováno v:
Statistica Neerlandica. 66:111-120
In this note, we will consider the problem of recovering an unknown input function when the output function is observed in its entirety, blurred with functional error. An estimator is constructed whose risk converges at an optimal rate. In this funct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e413a59428e2da1fa9ab3d7c6c9391e7
https://doi.org/10.1111/j.1467-9574.2011.00498.x
https://doi.org/10.1111/j.1467-9574.2011.00498.x
Publikováno v:
Mathematical Methods of Statistics. 20:232-245
In this paper some useful mathematical tools for the analysis of functional data are applied to the problem of testing the equality of two covariance operators. The test to be used is derived from a univariate likelihood ratio test in conjunction wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c00e7c2a911082b273e30df50e97e2ca
https://doi.org/10.3103/s1066530711030057
https://doi.org/10.3103/s1066530711030057
Publikováno v:
Journal of Multivariate Analysis. 99(5):815-833
In this paper tests are derived for testing neighborhood hypotheses for the one- and multi-sample problem for functional data. Our methodology is used to generalize testing in projective shape analysis, which has traditionally involving data consisti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08a8eb4248aa4cf792d6169f6f449fa4
Publikováno v:
Mathematical Methods of Statistics. 17:35-43
In this paper the well-known insurance ruin problem is reconsidered. The ruin probability is estimated in the case of an unknown claims density, assuming a sample of claims is given. An important step in the construction of the estimator is the appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5c01a506ea50251050307e5f637400f
https://doi.org/10.3103/s1066530708010031
https://doi.org/10.3103/s1066530708010031
Publikováno v:
Journal of Statistical Planning and Inference. 137:811-820
Nonparametric regression—directly or indirectly observed—is one of the important statistical models. On one hand it contains two infinite dimensional parameters (the regression function and the error density), and on the other it is of rather sim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::647322530ede83be45fc5f5da6dbbdd9
https://doi.org/10.1016/j.jspi.2006.06.030
https://doi.org/10.1016/j.jspi.2006.06.030
Publikováno v:
SIAM Journal on Numerical Analysis. 45:2610-2636
Previously, the convergence analysis for linear statistical inverse problems has mainly focused on spectral cut-off and Tikhonov-type estimators. Spectral cut-off estimators achieve minimax rates for a broad range of smoothness classes and operators,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c33a1aa18aef2a1625edd55bb9f20afe
https://doi.org/10.1137/060651884
https://doi.org/10.1137/060651884
Autor:
Frits H. Ruymgaart, André Mas
Publikováno v:
Complex Analysis and Operator Theory
Complex Analysis and Operator Theory, Springer Verlag, 2015, 9 (1), pp.35-63. ⟨10.1007/s11785-014-0371-5⟩
Complex Analysis and Operator Theory, Springer Verlag, 2015, 9 (1), pp.35-63. ⟨10.1007/s11785-014-0371-5⟩
The principal component analysis (PCA) is a famous technique from multivariate statistics. It is frequently carried out in dimension reduction either for functional data or in a high dimensional framework. To that aim PCA yields the eigenvectors $$\l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9c19fe0bb9dbb83c7d31a96d7dd24bd
https://hal.archives-ouvertes.fr/hal-00772880
https://hal.archives-ouvertes.fr/hal-00772880
