996 research outputs found
Partially linear models on Riemannian manifolds
In partially linear models the dependence of the response y on (x^T,t) is
modeled through the relationship y=\x^T \beta+g(t)+\epsilon where \epsilon is
independent of (x^T,t). In this paper, estimators of \beta and g are
constructed when the explanatory variables t take values on a Riemannian
manifold. Our proposal combine the flexibility of these models with the complex
structure of a set of explanatory variables. We prove that the resulting
estimator of \beta is asymptotically normal under the suitable conditions.
Through a simulation study, we explored the performance of the estimators.
Finally, we applied the studied model to an example based on real dataset.Comment: 7 pages, 2 figure
Empirical likelihood based testing for regression
Consider a random vector and let . We are interested
in testing for some known function , some compact set
IR and some function set of real valued
functions. Specific examples of this general hypothesis include testing for a
parametric regression model, a generalized linear model, a partial linear
model, a single index model, but also the selection of explanatory variables
can be considered as a special case of this hypothesis. To test this null
hypothesis, we make use of the so-called marked empirical process introduced by
\citeD and studied by \citeSt for the particular case of parametric regression,
in combination with the modern technique of empirical likelihood theory in
order to obtain a powerful testing procedure. The asymptotic validity of the
proposed test is established, and its finite sample performance is compared
with other existing tests by means of a simulation study.Comment: Published in at http://dx.doi.org/10.1214/07-EJS152 the Electronic
Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of
Mathematical Statistics (http://www.imstat.org
The bootstrap -A review
The bootstrap, extensively studied during the last decade, has become a powerful tool in different areas of Statistical Inference. In this work, we present the main ideas of bootstrap methodology in several contexts, citing the most relevant contributions and illustrating with examples and simulation studies some interesting aspects
Análisis multidisciplinar de la delincuencia socioeconómica
Traballo fin de grao (UDC.DER). Dereito. Curso 2012/201
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