Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Jureckova, Jana"'
Various indicators and measures of the real life procedures rise up as functionals of the quantile process of a parent random variable Z. However, Z can be observed only through a response in a linear model whose covariates are not under our control
Externí odkaz:
http://arxiv.org/abs/2404.02764
Our primary aim is to find an estimate of the expected shortfall in various situations: (1) Nonparametric situation, when the probability distribution of the incurred loss is unknown, only satisfying some general conditions. Then, following [3], the
Externí odkaz:
http://arxiv.org/abs/2212.12419
Autor:
Jurečková, Jana
We consider the linear regression model along with the process of its $\alpha$-regression quantile, $0<\alpha<1$. We are interested mainly in the slope components of $\alpha$-regression quantile and in their dependence on the choice of $\alpha.$ Whil
Externí odkaz:
http://arxiv.org/abs/2106.04373
In the linear regression model with possibly autoregressive errors, we propose a family of nonparametric tests for regression under a nuisance autoregression. The tests avoid the estimation of nuisance parameters, in contrast to the tests proposed in
Externí odkaz:
http://arxiv.org/abs/2007.12124
We consider semiparametric moment condition models invariant to transformation groups. The parameter of interest is estimated by minimum empirical divergence approach, introduced by Broniatowski and Keziou (2012). It is shown that the minimum empiric
Externí odkaz:
http://arxiv.org/abs/1904.11823
The processes of the averaged regression quantiles and of their modifications provide useful tools in the regression models when the covariates are not fully under our control. As an application we mention the probabilistic risk assessment in the sit
Externí odkaz:
http://arxiv.org/abs/1710.06638
Autor:
Jureckova, Jana
Various events in the nature, economics and in other areas force us to combine the study of extremes with regression and other methods. A useful tool for reducing the role of nuisance regression, while we are interested in the shape or tails of the b
Externí odkaz:
http://arxiv.org/abs/1512.01382
Publikováno v:
Journal of the Indian Statistical Association, Vol. 51 No. 1, 2013, 201-229
For some variants of regression models, including partial, measurement error or error-in-variables, latent effects, semi-parametric and otherwise corrupted linear models, the classical parametric tests generally do not perform well. Various modificat
Externí odkaz:
http://arxiv.org/abs/1503.07003
In the multivariate one-sample location model, we propose a class of flexible robust, affine-equivariant L-estimators of location, for distributions invoking affine-invariance of Mahalanobis distances of individual observations. An involved iteration
Externí odkaz:
http://arxiv.org/abs/1503.05392
Publikováno v:
Bernoulli 2016, Vol. 22, No. 2, 1093-1112
As was shown recently, the measurement errors in regressors affect only the power of the rank test, but not its critical region. Noting that, we study the effect of measurement errors on R-estimators in linear model. It is demonstrated that while an
Externí odkaz:
http://arxiv.org/abs/1411.3609