排序方式: 共有35条查询结果,搜索用时 406 毫秒
1.
Hyeyoung Maeng 《统计学通讯:理论与方法》2017,46(3):1144-1157
Bootstrap forecast intervals are developed for volatilities having asymmetric features, which are accounted for by fitting EGARCH models. A Monte-Carlo simulation compares the proposed forecast intervals with those based on GARCH fittings which ignore asymmetry. The comparison reveals substantial advantage of addressing asymmetry through EGARCH fitting over ignoring it as the conventional GARCH forecast. The EGARCH forecast intervals have empirical coverage probabilities closer to the nominal level and/or have shorter average lengths than the GARCH forecast intervals. The finding is also supported by real dataset analysis of Dow–Jones index and financial times stock exchange (FTSE) 100 index. 相似文献
2.
Pablo Martínez-Camblor 《Journal of applied statistics》2011,38(6):1117-1131
The traditional Cramér–von Mises criterion is used in order to develop a test to compare the equality of the underlying lifetime distributions in the presence of independent censoring times. Its asymptotic distribution is proved and a resampling plan, which is valid for unbalanced data situations, is proposed. Its statistical power is studied and compared with commonly used linear rank tests by Monte Carlo simulations and a real data analysis is also considered. It is observed that the new test is clearly more powerful than the traditional ones when there exists no uniform dominance among involved distributions and in the presence of late differences. Its statistical power is also good in the other considered scenarios. 相似文献
3.
Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias. 相似文献
4.
Dong Wan Shin 《Statistics》2015,49(1):209-223
Stationary bootstrapping is applied to panel cointegration tests which are based on the ordinary least-squares estimator and the seemingly unrelated regression (SUR) estimator of the residual unit root. Large sample validity of stationary bootstrapping is established. A finite sample experiment reveals that size performances of the bootstrap tests are much less sensitive to cross-sectional correlation than those of existing tests and a test based on the SUR estimator has substantially better power than existing tests. 相似文献
5.
ABSTRACTRegression analysis is one of the important tools in statistics to investigate the relationships among variables. When the sample size is small, however, the assumptions for regression analysis can be violated. This research focuses on using the exact bootstrap to construct confidence intervals for regression parameters in small samples. The comparison of the exact bootstrap method with the basic bootstrap method was carried out by a simulation study. It was found that on a very small sample (n ≈ 5) under Laplace distribution with the independent variable treated as random, the exact bootstrap was more effective than the standard bootstrap confidence interval. 相似文献
6.
Denis Heng-Yan Leung & You-Gan Wang 《Australian & New Zealand Journal of Statistics》1998,40(1):43-52
The paper studies stochastic approximation as a technique for bias reduction. The proposed method does not require approximating the bias explicitly, nor does it rely on having independent identically distributed (i.i.d.) data. The method always removes the leading bias term, under very mild conditions, as long as auxiliary samples from distributions with given parameters are available. Expectation and variance of the bias-corrected estimate are given. Examples in sequential clinical trials (non-i.i.d. case), curved exponential models (i.i.d. case) and length-biased sampling (where the estimates are inconsistent) are used to illustrate the applications of the proposed method and its small sample properties. 相似文献
7.
Shiquan Ren Hong Lai Wenjing Tong Mostafa Aminzadeh Xuezhang Hou Shenghan Lai 《Journal of applied statistics》2010,37(9):1487-1498
Nonparametric bootstrapping for hierarchical data is relatively underdeveloped and not straightforward: certainly it does not make sense to use simple nonparametric resampling, which treats all observations as independent. We have provided some resampling strategies of hierarchical data, proved that the strategy of nonparametric bootstrapping on the highest level (randomly sampling all other levels without replacement within the highest level selected by randomly sampling the highest levels with replacement) is better than that on lower levels, analyzed real data and performed simulation studies. 相似文献
8.
Galen R. Shorack 《统计学通讯:理论与方法》2013,42(9):961-972
The bootstrap principle is justified for. robust M-estimates in regression, (A short proof justifying bootstrapping the empirical process is also given.) 相似文献
9.
Consider a finite population u , which can be viewed as a realization of a super-population model. A simple ratio model (linear regression, without intercept) with heteroscedastic errors is supposed to have generated u . A random sample is drawn without replacement from u . In this set-up a two-stage wild bootstrap resampling scheme as well as several other useful forms of bootstrapping in finite populations will be considered. Some asymptotic results for various bootstrap approximations for normalized and Studentized versions of the well-known ratio and regression estimator are given. Bootstrap based confidence interval s for the population total and for the regression parameter of the underlying ratio model are also discussed 相似文献
10.
王国治 《华南理工大学学报(社会科学版)》2011,13(4):33-36,73
运用经典的和修正过的重标极差方法研究了在1999到2009上证指数中的波动率和收益率的长期依赖关系。运用具有预白(pre-whitening)和后黑(postblackening)的Moving block bootstrap方法为假设检验构建置信区间。结果显示上证指数的收益率没有显著的长期相关。但是,波动率具有显著的长期相关。关于收益率的研究和之前一些研究提出的中国股票市场具有可持续性的结论相抵触。并且,之前这方面的研究大多数没有运用置信区间或只是基于标准正态分布的置信区间。因此,这些研究的结果需要从新检验和从新进行解释。 相似文献