BootsModelTest(sac)
BootsModelTest()所属R语言包:sac
Bootstrap Test of the Validity of the Semiparametric Change-Point Model
引导测试的半参数变点模型的有效性
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Using bootstrap method to approximate the p-value of test of the model validity. Bootstrap samples are drawn from the semiparametrica empirical distribution which are estimates of the underlying population distributions.
使用自举的方法来近似p价值的测试模型的有效性。 bootstrap样本都是来自semiparametrica经验分布,这是底层人口分布的估计。
用法----------Usage----------
BootsModelTest(x, k, m, B, Alpha, Beta, tol = 1.0e-7, maxit=50, trace=FALSE)
参数----------Arguments----------
参数:x
a numeric vector or matrix containing the data, one row per observation;
包含的数据,每一个行观察的一个数值向量或矩阵;
参数:k
the estimated change-point, output of SemiparChangePoint
估计变点,输出SemiparChangePoint
参数:m
= n the sample size for "one-change" alternative, or the estimated second change-point for "epidemic" alternative, an output of SemiparChangePoint
=n"one-change"替代,或估计第二个变化点"epidemic"替代,输出SemiparChangePoint的样本量
参数:B
number of resamples
数量的重新采样
参数:Alpha
estimated parameter alpha, output of SemiparChangePoint
估计参数alpha,SemiparChangePoint输出
参数:Beta
estimated parameter beta, output of SemiparChangePoint
估计参数beta,SemiparChangePoint输出
参数:tol
the desired accuracy (convergence tolerance), an argument of glm.control.
所需的精度(收敛公差)的参数glm.control。
参数:maxit
the maximum number of iterations, an argument of glm.control.
最大的迭代次数的参数glm.control。
参数:trace
logical indicating if output should be produced for each iteration, an argument of glm.control.
逻辑表明,如果输出应为每次迭代中,一个参数的glm.control。
值----------Value----------
<table summary="R valueblock"> <tr valign="top"><td>Delta </td> <td> The test statistic of the model validity</td></tr> <tr valign="top"><td>Pvalue </td> <td> The bootstrapped p-value </td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD>Delta </ TD> <TD>模型的有效性的检验统计量</ TD> </ TR> <TR VALIGN =“”> <TD>Pvalue </ TD> <TD>的自举p-值</ TD> </ TR> </ TABLE>
(作者)----------Author(s)----------
Zhong Guan <a href="mailto:zguan@iusb.edu">zguan@iusb.edu</a>
参考文献----------References----------
Guan, Z.(2001) Some Results About Empirical Likelihood Method, Ph.D. Thesis, The University of Toledo.
Guan, Z.(2004) A semiparametric changepoint model, Biometrika, 91, 4, 849–862.
Guan, Z. Semiparametric Tests for Change-points with Epidemic Alternatives.
参见----------See Also----------
SemiparChangePoint, schapt
SemiparChangePoint,schapt
实例----------Examples----------
## Nile data with one change-point: the annual flows drop in 1898.[#尼罗河的一个变化点:每年流量下降,1898年的数据。]
## It is believed to be caused by the building of the first Aswan dam.[#这被认为是第一阿斯旺大坝的建设所造成的。]
if(! "package:stats" %in% search()) library(stats)
data(Nile)
require(sac) #load the package[加载包]
Nile.res<-SemiparChangePoint(Nile, alternative = "one.change")
BootsModelTest(Nile, Nile.res$k.hat, length(Nile), B=5, Nile.res$alpha.hat,
Nile.res$beta.hat)
# Choose larger B to get better approximate p-value.[选择较大的B小p值更接近。]
# It takes longer to do bootstrap model test for large B.[它需要更长的时间做引导模型试验大B.]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
注2:由于是机器人自动翻译,难免有不准确之处,使用时仔细对照中、英文内容进行反复理解,可以帮助R语言的学习。
注3:如遇到不准确之处,请在本贴的后面进行回帖,我们会逐渐进行修订。
|