davies.test(segmented)
davies.test()所属R语言包：segmented
Testing for a change in the slope
测试中的斜率的变化
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Given a generalized linear model, the Davies' test can be employed to test for a non-constant regression parameter in the linear predictor.
广义线性模型，戴维斯的测试可以用来测试中的线性预测的非恒定回归参数。
用法----------Usage----------
davies.test(obj, seg.Z, k = 10, alternative = c("two.sided",
"less", "greater"), beta0=0, dispersion=NULL)
参数----------Arguments----------
参数：obj
a fitted model returned by glm or lm.
一个拟合模型返回的glm或lm。
参数：seg.Z
a formula with no response variable, such as seg.Z=~x1, indicating the (continuous) segmented variable being tested. Only a single variable may be tested and a warning is printed when seg.Z includes two or more terms.
没有响应变量的公式，如seg.Z=~x1，表明测试（连续）分段变量。只有一个变量可以进行测试时打印seg.Z包含两个或两个以上条款，并发出警告。
参数：k
number of points where the test should be evaluated. See details.
应评估测试的点的数目。查看详细信息。
参数：alternative
a character string specifying the alternative hypothesis.
一个字符串指定其他假设。
参数：beta0
the null value of the difference-in-slope; default to zero meaning no breakpoint, see details.
差异的斜率，默认的空值为零，意味着没有断点，查看详细信息。
参数：dispersion
the dispersion parameter for the family to be used to compute the Wald statistic. When NULL (the default), it is inferred from obj. Namely it is taken as 1 for the binomial and Poisson families, and otherwise estimated by the residual Chi-squared statistic (calculated from cases with non-zero weights) divided by the residual degrees of freedom.
为家庭的分散参数被用于计算Wald统计量。当NULL（默认值），它推断出obj。即它是作为1为二项分布和泊松家庭的，否则估计的剩余除以残差自由度的卡方统计（计算结果与非零权重的情况下）。
Details
详细信息----------Details----------
davies.test tests for a non zero difference-in-slope parameter of a segmented relationship. Namely, the null hypothesis is H_0:beta=beta0, where beta is the difference-in-slope, i.e. the coefficient of the segmented function beta*(x-psi)_+, and beta0 is the "null" value specified via the argument beta0. Roughtly speaking, the procedure computes k "naive" (i.e. assuming fixed and known the breakpoint) Wald statistics for the difference-in-slope, seeks the "best" value (according to the alternative hypothesis), and then corrects the selected (minimum) p-value. The k evaluation points are k equally spaced values between the 0.05 and 0.95 quantiles of the variable reported in seg.Z.
davies.test测试为非零差在一个分段的关系的斜率参数。也就是说，零假设是H_0:beta=beta0，beta是的差别斜率，即系数的分段函数beta*(x-psi)_+，beta0是空数值通过参数beta0。大概被来讲，程序计算k天真（即假设固定的和已知的断点）Wald统计量的差异坡，旨在“最好”的值（根据备择假设），然后校正所选的（最小的）p-值。 k评估点k等距值在0.05和0.95之间位数的变量在seg.Z。
值----------Value----------
A list with class 'htest' containing the following components:
列表类的htest包含以下组件：
参数：method
title (character)
标题（字符）
参数：data.name
the regression model and the segmented variable being tested
回归模型和分段变量测试
参数：statistic
the point at which the maximum (or the minimum if alternative="less") occurs
点的最大（或最小如果alternative="less"）发生
参数：parameter
number of evaluation points
评价点的数量
参数：p.value
the adjusted p-value
调整后的p-值
参数：process
a two-column matrix including the evaluation points and corresponding values of the statistic
一个两列的矩阵，包括评价点和对应的统计值
注意----------Note----------
Strictly speaking, the Davies test is not confined to the segmented regression; the procedure can be applied when a nuisance parameter vanishes under the null hypothesis. The test is slightly conservative, as the computed p-value is actually an upper bound.
严格地说，戴维斯测试并不局限于分段回归滋扰参数时，可以应用的零假设下消失的过程。本试验是稍微保守的，因为所计算的p-值是实际的上限。
（作者）----------Author(s)----------
Vito M.R. Muggeo
参考文献----------References----------
实例----------Examples----------
## Not run: set.seed(20)[＃不运行：set.seed的（20）]
z<-runif(100)
x<-rnorm(100,2)
y<-2+10*pmax(z-.5,0)+rnorm(100,0,2)
o<-lm(y~z+x)
davies.test(o,~z)
davies.test(o,~x)
## End(Not run)[＃（不执行）]
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。
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发表于 2012-9-30 00:21:56
