***#>#> AWB bootstrap sequential quantile union test#>#> data: MacroTS#> null hypothesis: Series has a unit root#> alternative hypothesis: Series is stationary#>#> Sequence of tests:#> H0: # I(0) H1: # I(0) tstat p-value#> Step 1 0 5 -1.052 0.05013 Bootstrap FDR Controlling...
We note that while there exist approaches that do not employ out-of-sample estimation, such as using the Akaike Information Criterion (AIC) (Akaike 1974) of the models, the Bayesian Information Criterion (BIC) (Schwarz 1978), and others, in this paper we focus only on out-of-sample ...
where the models are presented according to their AIC. I shall copy here one advertisement given in the help page for this function It is important to note that the models fitted by this function is only a small fraction of the models possible with PhyML. For instance, it is possible to...
I do the bootstrapping with the aid of thebootpackage, which is generally the recommended approach in R. For repeated cross-validation of the two straightforward strategies (full model and stepwise variable selection) I use thecaretpackage, in combination withstepAICwhich is in the Venables and ...
Latent class (LC) analysis is used to construct empirical evidence on the existence of latent subgroups based on the associations among a set of observed discrete variables. One of the tests used to infer about the number of underlying subgroups is the bootstrap likelihood ratio test (BLRT). ...
The well-known Akaike Information Criterion (AIC) cannot be directly applied since AIC is based on maximum likelihood estimation while GEE is nonlikelihood based. We propose a modification to AIC, where the likelihood is replaced by the quasi-likelihood and a proper adjustment is made for the ...
The existence of cross-sectional dependence in these countries means that it is justified to use the Bootstrap Panel Granger Causality method in Kónya (2006). For each system of equations the number of lags was chosen according to the AIC and SC criterion (We used the AIC criterion to compa...
Bootstrapping generalized linear models Several methods for bootstrapping generalized linear regression models are introduced. One-step techniques, both conditional and unconditional on the covar... LH Moulton,SL Zeger - 《Computational Statistics & Data Analysis》 被引量: 79发表: 1991年 加载更多研究...
In step two, a backward AR(1) regression is fitted, and random blocks of residuals are used to generate the bootstrap replicate. In step three the bootstrap replicate is used to run the AR(1) regression again and random blocks of residuals are used to compute the bootstrap out-of-...
如果我们按照图表进行拟合,将有太多参数无法拟合。一种解决方案是使用每周或每月图表。...在这里,我们将最大滞后时间限制为 5 天,并使用 AIC 选择最佳模型。...我们将 AR 滞后和 GARCH 滞后都限制为小于 5。结果最优阶为 (4,2,2)。...将第二个方程代入第一个方程很容易看出随机性,并将方程改写为...