Zobrazeno 1 - 10
of 123
pro vyhledávání: '"Victor J. Yohai"'
Publikováno v:
Journal of Statistical Software, Vol 92, Iss 1, Pp 1-23 (2020)
gdpc is an R package for the computation of the generalized dynamic principal components proposed in Peña and Yohai (2016). In this paper, we briefly introduce the problem of dynamical principal components, propose a solution based on a reconstructi
Externí odkaz:
https://doaj.org/article/5c3e4092ea5948e9b0cf6ea9cdb74f34
Publikováno v:
International Journal of Forecasting. 37:1498-1508
We present the sparse estimation of one-sided dynamic principal components (ODPCs) to forecast high-dimensional time series. The forecast can be made directly with the ODPCs or by using them as estimates of the factors in a generalized dynamic factor
Publikováno v:
TEST. 29:819-843
Doubly protected methods are widely used for estimating the population mean of an outcome Y from a sample where the response is missing in some individuals. To compensate for the missing responses, a vector $$\mathbf {X}$$ of covariates is observed a
Publikováno v:
Communications in Statistics - Theory and Methods. 47:5145-5162
In this paper, we propose a new procedure to estimate the distribution of a variable y when there are missing data. To compensate the presence of missing responses, it is assumed that a covariate vector x is observed and that y and x are related by m
Generalized Linear Models are routinely used in data analysis. Classical estimators are based on the maximum likelihood principle and it is well known that the presence of outliers can have a large impact on them. Several robust procedures have been
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b56ccc2c1686b9906ef44da51057eb1
https://www.sciencedirect.com/science/article/pii/S0167947318302895?via=ihub
https://www.sciencedirect.com/science/article/pii/S0167947318302895?via=ihub
Autor:
Victor J. Yohai, Ricardo A. Maronna
Let F_{{\theta}} be a family of distributions with support on the set of nonnegative integers Z_0. In this paper we derive the M-estimators with smallest gross error sensitivity (GES). We start by defining the uniform median of a distribution F with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee4818c3da7a9baeab95ba5ea599547b
Publikováno v:
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
We define one-sided dynamic principal components (ODPC) for time series as linear combinations of the present and past values of the series that minimize the reconstruction mean squared error. Usually dynamic principal components have been defined as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0f1faa2b67e31d73f2b23ddaea6f250
Autor:
Victor J. Yohai, Ricardo A. Maronna
Publikováno v:
Encyclopedia of Statistical Sciences
Classical methods in multivariate analysis require the estimation of means and covariance matrices. Although the sample mean and covariance matrix are optimal estimates of multivariate location and scatter when the data are multivariate normal, a sma
Autor:
Victor J. Yohai, Marina Valdora
Publikováno v:
Statistics & Probability Letters. 162:108751
M estimators based on the probability integral transformation for discrete distributions are introduced and their asymptotic properties are proved. The proposed estimators are applied to count data in a simulation study and in a real data set of hosp
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well w