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2.
Xiaojing Xiang 《Annals of the Institute of Statistical Mathematics》1995,47(1):105-117
A necessary condition for the asymptotic normality of the sample quantile estimator isf(Q(p))=F(Q(p))>0, whereQ(p) is thep-th quantile of the distribution functionF(x). In this paper, we estimate a quantile by a kernel quantile estimator when this condition is violated. We have shown that the kernel quantile estimator is asymptotically normal in some nonstandard cases. The optimal convergence rate of the mean squared error for the kernel estimator is obtained with respect to the asymptotically optimal bandwidth. A law of the iterated logarithm is also established.This research was partially supported by the new faculty award from the University of Oregon. 相似文献
3.
考虑一类"中度偏离"单位根过程,y_t=q_ny_t-1+u_t,其中qn=1+c/(k_n),k_n=o(n),c为一非零常数,{u_t}为随机扰动项序列.在允许扰动项方差无穷的条件下,构造q_n的复合分位数估计,并得到了该估计的渐近分布.最后通过数值模拟,在扰动项服从t(2)分布下,说明了该估计的稳健和有效性. 相似文献
4.
For linear quantile regression model, this paper proves that the test statistics, besed on smoothed empirical likelihood (SEL) method and least absolute deviation (LAD) method, both converge weakly to a noncentral Chi-square distribution under the local alternatives $H_1:\beta=\beta_0+a_n$, where $\beta$ is the true parameter. Simulation results show that the SEL method is more efficient than the LAD method. 相似文献
5.
How to choose an optimal threshold is a key problemin the generalized Pareto distribution (GPD) model.This paper attains the exactthreshold by testing for GPD,and shows that GPD model allows the actuary to easily estimate high quantiles and the probable maximum loss from the medical insurance claims data. 相似文献
6.
J. K. Ghorai 《Annals of the Institute of Statistical Mathematics》1991,43(4):747-760
The problem of estimating a smooth quantile function, Q(·), at a fixed point p, 0 < p < 1, is treated under a nonparametric smoothness condition on Q. The asymptotic relative deficiency of the sample quantile based on the maximum likelihood estimate of the survival function under the proportional hazards model with respect to kernel type estimators of the quantile is evaluated. The comparison is based on the mean square errors of the estimators. It is shown that the relative deficiency tends to infinity as the sample size, n, tends to infinity. 相似文献
7.
分位点函数的光滑非参数估计的BAHADUR表示 总被引:1,自引:0,他引:1
文中对分位函数给出了具有更广泛应用的光滑分位估计,证明了该光滑分位估计的逐点和一致的Bahadur强表示定理;并由此结果推导了估计的重对数律,强逼近等深刻结果。 相似文献
8.
Heavy tailed durations of regional rainfall 总被引:1,自引:0,他引:1
Durations of rain events and drought events over a given region provide important information about the water resources of
the region. Of particular interest is the shape of upper tails of the probability distributions of such durations. Recent
research suggests that the underlying probability distributions of such durations have heavy tails of hyperbolic type, across
a wide range of spatial scales from 2 km to 120 km. These findings are based on radar measurements of spatially averaged rain
rate (SARR) over a tropical oceanic region. The present work performs a nonparametric inference on the Pareto tail-index of
wet and dry durations at each of those spatial scales, based on the same data, and compares it with conclusions based on the
classical Hill estimator. The results are compared and discussed.
The authors express sincere thanks to the Mathematisches Forschungsinstitut Oberwolfach (MFO) for facilitating their collaboration
under a “Research in Pairs” project hosted at MFO during March 5–25, 2006. The research of the second and third authors was supported by the project
LC06024. 相似文献
9.
The importance of variable selection and regularization procedures in multiple regression analysis cannot be overemphasized. These procedures are adversely affected by predictor space data aberrations as well as outliers in the response space. To counter the latter, robust statistical procedures such as quantile regression which generalizes the well-known least absolute deviation procedure to all quantile levels have been proposed in the literature. Quantile regression is robust to response variable outliers but very susceptible to outliers in the predictor space (high leverage points) which may alter the eigen-structure of the predictor matrix. High leverage points that alter the eigen-structure of the predictor matrix by creating or hiding collinearity are referred to as collinearity influential points. In this paper, we suggest generalizing the penalized weighted least absolute deviation to all quantile levels, i.e., to penalized weighted quantile regression using the RIDGE, LASSO, and elastic net penalties as a remedy against collinearity influential points and high leverage points in general. To maintain robustness, we make use of very robust weights based on the computationally intensive high breakdown minimum covariance determinant. Simulations and applications to well-known data sets from the literature show an improvement in variable selection and regularization due to the robust weighting formulation. 相似文献
10.
Dan Zaelit 《商业与工业应用随机模型》2014,30(3):271-293
We use proprietary data collected by SVB Analytics, an affiliate of Silicon Valley Bank, to forecast the retained earnings of privately held companies. Combining methods of principal component analysis (PCA) and L1/quantile regression, we build multivariate linear models that feature excellent in‐sample fit and strong out‐of‐sample predictive accuracy. The combined PCA and L1 technique effectively deals with multicollinearity and non‐normality of the data, and also performs favorably when compared against a variety of other models. Additionally, we propose a variable ranking procedure that explains which variables from the current quarter are most predictive of the next quarter's retained earnings. We fit models to the top five variables identified by the ranking procedure and thereby, discover interpretable models with excellent out‐of‐sample performance. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献