line.cis(smatr)
line.cis()所属R语言包：smatr
Slope and elevation of a (standardised) major axis, with confidence intervals
坡度和海拔的（标准）的主要轴线，与置信区间
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculates the slope and elevation of a major axis or standardised
计算坡度和海拔的长轴或标准化
用法----------Usage----------
line.cis(y, x, alpha = 0.05, data = NULL,
method = "SMA", intercept = TRUE, robust=FALSE,
V = matrix(0, 2, 2), f.crit = 0, ...)
参数----------Arguments----------
参数：y
The Y-variable
的Y变量
参数：x
The X-variable
的X-变量
参数：alpha
The desired confidence level for the 100(1-alpha)% confidence interval for the common slope. (Default value is 0.05, which returns a 95% confidence interval.)
所需的置信水平为100（1-α）％置信区间为共同斜率。 （默认值是0.05，它返回一个95％的置信区间）。
参数：data
(optional) data frame containing the data
（可选的）数据框包含的数据
参数：method
The line fitting method:
该生产线拟合的方法：
'OLS' or 0linear regression
“OLS或0linear的回归
'SMA' or 1standardised major axis (this is the default)
“SMA”或1standardised长轴（这是默认设置）
'MA' or 2major axis
MA或2major轴的
参数：V
The estimated variance matrix of measurement error. Average measurement error for Y is in the first row and column, and average measurement error for X is in the second row and column. The default is that there is no measurement error.
估计方差矩阵的测量误差。平均测量误差为Y中的第一行和列，和用于X的平均测量误差是在第二行和列。在默认情况下是不存在测量误差。
参数：intercept
(logical) Whether or not the line includes an intercept.
（逻辑）是否该系列包括拦截。
FALSE no intercept, so the line is forced through the origin
FALSE没有拦截，因此被强制通过原点
TRUE an intercept is fitted (this is the default)
TRUE拦截安装（这是默认的）
参数：robust
If TRUE, uses a robust method to fit the lines.
如果为true，则使用一种稳健的方法，以适应行。
参数：f.crit
(optional - rarely required). The critical value to be used from the F distribution. (Only actually useful for reducing computation time in simulation work - otherwise, do not change.)
（可选的 - 很少需要）。的临界值被用于从F分布。 （实际上只减少计算时间，在模拟工作 - 否则，不改变）。
参数：...
Further parameters (not passed anywhere at the moment).
其他参数（不通过任何地方的时刻）。
Details
详细信息----------Details----------
Fits a linear regression line, major axis, or standardised major axis, to a bivariate dataset. The slope and elevation are returned with confidence intervals, using any user-specified confidence level.
适合的线性回归线，长轴，或标准化的长轴，至二元数据集。坡度和海拔的置信区间，返回使用任何用户指定的置信水平。
Confidence intervals are constructed by inverting the standard one-sample tests for elvation and slope (see slope.test and elev.test for more details). Only the primary confidence interval is returned - this is valid as long as it is known a priori that the (standardised) major axis is estimating the true slope rather than the (standardised) minor axis. For SMA, this means that the sign of the true slope needs to be known a priori, and the sample slope must have the same sign as the true slope.
置信区间的构造反相的标准样本检验的elvation和斜率（看到slope.test elev.test更多详细信息）。只有主置信区间返回 - 这是有效的，只要它是先验已知的，（标准化）的长轴估计真正的斜率，而不是（标准化）短轴。 SMA的，这意味着，真正的斜率的符号需要先验已知的，和样品斜率必须具有相同的符号，作为真实的斜率。
If measurement error is present, it can be corrected for through use of the input argument V, which makes adjustments to the estimated sample variances and covariances then proceeds with the same method of inference. Note, however, that this method is only approximate (see Warton et al in review for more details).
如果测量误差是存在的，它可以通过使用输入的参数V，使具有相同的推理方法的调整的估计的样本方差和协方差然后前进校正。但是，请注意，这种方法只是近似（有关详细信息，沃顿等人在审查）。
The test assumes the following:
测试假设如下：
y and x are linearly related
y和x是线性相关的
residuals independently follow a normal distribution with equal variance at all points along the line
残差独立遵循正态分布，等方差沿线的所有点
These assumptions can be visually checked by plotting residuals against fitted axis scores, and by constructing a Q-Q plot of residuals against a normal distribution. An appropriate residual variable is y-bx, and for fitted axis scores use x (for linear regression), y+bx (for SMA) or by+x (for MA), where b represents the estimated slope.
这些假设可以用肉眼检查，通过绘制残差对装轴的分数，并通过对一个正态分布的残差构造的QQ图。一个适当的残差变量是y-BX，和用于拟合轴线分数使用×（线性回归）中，y + BX（SMA）或+×（MA），其中b代表估计斜率。
值----------Value----------
参数：coeff
A matrix containing the estimated elevation and slope (first column), and the lower and upper limits of confidence intervals for the true elevation and slope (second and third columns). Output for the elevation and slope are in the first and second rows, respectively.
含A矩阵估计的仰角和斜率（第一列），与真实的高度和斜率（第二列和第三列）的置信区间的下限和上限的。海拔和坡度的输出是分别在第一和第二行，。
（作者）----------Author(s)----------
Warton, D. <a href="mailto avid.Warton@unsw.edu.au">David.Warton@unsw.edu.au</a>, translated to R by Ormerod, J. 2005-12-08
参考文献----------References----------
参见----------See Also----------
sma, slope.test, elev.test
sma，slope.test，elev.test
实例----------Examples----------
#load the leaflife data[加载leaflife数据]
data(leaflife)
#consider only the low rainfall sites:[考虑只有低降雨网站：]
leaf.low.rain=leaflife[leaflife$rain=='low',]
#estimate the SMA line for reserve vs coat[估计SMA线储备与外套]
line.cis(log10(longev),log10(lma),data=leaf.low.rain)
#produce CI's for MA slope and elevation:[产生CI的MA坡度和海拔的：]
line.cis(log10(longev),log10(lma),data=leaf.low.rain, method='MA')
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。
|
发表于 2012-9-30 10:13:47
