Calculus of the estimators of linear quantile regression by the method ACCPM.
Censored regression models with double exponential error distributions: an iterattive estimation procedure based on medians for correcting bias.
In this paper, we consider a simple iterative estimation procedure for censored regression models with symmetrical exponential error distributions. Although each step requires to impute the censored data with conditional medians, its tractability is guaranteed as well as its convergence at geometrical rate. Finally, as the final estimate coincides with a Huber M-estimator, its consistency and asymptotic normality are easily proved.
Changepoint estimation for dependent and non-stationary panels
The changepoint estimation problem of a common change in panel means for a very general panel data structure is considered. The observations within each panel are allowed to be generally dependent and non-stationary. Simultaneously, the panels are weakly dependent and non-stationary among each other. The follow up period can be extremely short and the changepoint magnitudes may differ across the panels accounting also for a specific situation that some magnitudes are equal to zero (thus, no jump...
Change-point estimator in continuous quadratic regression
The paper deals with the asymptotic distribution of the least squares estimator of a change point in a regression model where the regression function has two phases --- the first linear and the second quadratic. In the case when the linear coefficient after change is non-zero the limit distribution of the change point estimator is normal whereas it is non-normal if the linear coefficient is zero.
Change-point estimator in gradually changing sequences
Recently Hušková (1998) has studied the least squares estimator of a change-point in gradually changing sequence supposing that the sequence increases (or decreases) linearly after the change-point. The present paper shows that the limit behavior of the change-point estimator for more complicated gradual changes is similar. The limit variance of the estimator can be easily calculated from the covariance function of a limit process.
Change-point problems: A Bayesian nonparametric approach
A change-point problem is examined from a Bayesian viewpoint, under nonparametric hypotheses. A Ferguson-Dirichlet prior is chosen and the posterior distribution is computed for the change-point and for the unknown distribution functions.
Change-Point problems: approaches and applications.
Problems of making inferences about abrupt changes in the mechanism underlying a sequence of observations are considered in both retrospective and on-line contexts. Among the topics considered are the Lindisfarne scribes problem; switching straight lines; manoeuvering targets, and shifts of level or slope in linear time series models. Summary analyses of data obtained in studies of schizophrenic and kidney transplant patients are presented.
Characterization of admissible linear estimators under extended balanced loss function
In this paper, we study the admissibility of linear estimator of regression coefficient in linear model under the extended balanced loss function (EBLF). The sufficient and necessary condition for linear estimators to be admissible are obtained respectively in homogeneous and non-homogeneous classes. Furthermore, we show that admissible linear estimator under the EBLF is a convex combination of the admissible linear estimator under the sum of square residuals and quadratic loss function.
Characterizations of Normality in Translation Classes by Properties of Bayes Estimators.
Charakterisierung der zweiseitigen Exponentialverteilung.
Chi-squared goodness-of-fit test for the family of logistic distributions
Choice of a Survival Model for Patients With a Brain Tumour.
Choosing the best -divergence goodness-of-fit statistic in multinomial sampling with linear constraints
In this paper we present a simulation study to analyze the behavior of the -divergence test statistics in the problem of goodness-of-fit for loglinear models with linear constraints and multinomial sampling. We pay special attention to the Rényi’s and -divergence measures.
Classical and bayesian approaches to the change-point problem : fixed sample and sequential procedures
Coefficient de corrélation et prise de décision
Combining forecasts using the least trimmed squares
Employing recently derived asymptotic representation of the least trimmed squares estimator, the combinations of the forecasts with constraints are studied. Under assumption of unbiasedness of individual forecasts it is shown that the combination without intercept and with constraint imposed on the estimate of regression coefficients that they sum to one, is better than others. A numerical example is included to support theoretical conclusions.
Commentaire à propos de «Lissage de fractile par M. Cramer»
Comments on: Natural Induction: An objective Bayesian approach.
Compact hypothesis and extremal set estimators
In extremal estimation theory the estimators are local or absolute extremes of functions defined on the cartesian product of the parameter by the sample space. Assuming that these functions converge uniformly, in a convenient stochastic way, to a limit function g, set estimators for the set ∇ of absolute maxima (minima) of g are obtained under the compactness assumption that ∇ is contained in a known compact U. A strongly consistent test is presented for this assumption. Moreover, when the true...
Comparación de curvas de supervivencia gamma estocásticamente ordenadas.
En este trabajo se propone un análisis de supervivencia basado en un modelo Gamma. Se obtienen las condiciones teóricas bajo las cuales dos funciones de supervivencia Gamma están estocásticamente ordenadas. Estos resultados se utilizan para proponer un método sencillo que permite comparar dos poblaciones cuando, a priori, se conoce que sus curvas de supervivencia están estocásticamente ordenadas. Los resultados se ejemplifican con el análisis de un banco de datos reales sobre tiempos de desempleo....