rcspline.plot(Hmisc)
rcspline.plot()所属R语言包：Hmisc
Plot Restricted Cubic Spline Function
绘制限制三次样条函数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Provides plots of the estimated restricted cubic spline function relating a single predictor to the response for a logistic or Cox model. The rcspline.plot function does not allow for interactions as do lrm and cph, but it can provide detailed output for checking spline fits. This function uses the rcspline.eval, lrm.fit, and Therneau's coxph.fit functions and plots the estimated spline regression and confidence limits, placing summary statistics on the graph. If there are no adjustment variables, rcspline.plot can also plot two alternative estimates of the regression function when model="logistic": proportions or logit proportions on grouped data, and a nonparametric estimate. The nonparametric regression estimate is based on smoothing the binary responses and taking the logit transformation of the smoothed estimates, if desired. The smoothing uses supsmu.
提供的预算约束下的三次样条函数的MF或Cox比例风险模型的响应与一个单一的预测图。 rcspline.plot函数不允许的相互作用做lrm和cph，但它可以提供详细的输出，检查样条拟合。此功能使用rcspline.eval，lrm.fit，和Therneau的coxph.fit函数和绘制样条回归估计和置信限，将图表上的汇总统计数据。如果没有调节变量，rcspline.plot也可以绘制两种可供选择的回归函数估计的当model="logistic"：比例或罗吉特分组数据的比例，和非参数估计。非参数回归估计的基础上平滑的二进制反应和采取的的罗吉特转型的平滑估计，如果需要的话。平滑使用supsmu。
用法----------Usage----------
rcspline.plot(x,y,model=c("logistic", "cox", "ols"), xrange, event, nk=5,
knots=NULL, show=c("xbeta","prob"), adj=NULL, xlab, ylab,
ylim, plim=c(0,1), plotcl=TRUE, showknots=TRUE, add=FALSE,
subset, lty=1, noprint=FALSE, m, smooth=FALSE, bass=1,
main="auto", statloc)
参数----------Arguments----------
参数：x
a numeric predictor
一个数字的预测
参数：y
a numeric response. For binary logistic regression, y should be either 0 or 1.
一个数字的反应。二分类Logistic回归，y应该是0或1。
参数：model
"logistic" or "cox". For "cox", uses the coxph.fit function with method="efron" arguement set.
"logistic"或"cox"。对于"cox"，coxph.fitmethod="efron"的arguement集功能与。
参数：xrange
range for evaluating x, default is <VAR>f</VAR> and 1 - \var{f} quantiles of x, where \var{f} = 10/max(\var{n}, 200)
范围评估x，默认情况下是<VAR> F </ VAR>和1 - \var{f}位数的x，\var{f} = 10/max(\var{n}, 200)
参数：event
event/censoring indicator if model="cox". If event is present, model is assumed to be "cox"
事件/审查指标，如果model="cox"。如果event是目前，model假定是"cox"
参数：nk
number of knots
节点数
参数：knots
knot locations, default based on quantiles of x (by rcspline.eval)
结的位置，默认情况下，根据位数的x（rcspline.eval）
参数：show
"xbeta" or "prob" - what is plotted on <PRE>y</PRE>-axis
"xbeta"或"prob" - 上绘制<PRE> </ PRE>轴
参数：adj
optional matrix of adjustment variables
可选的调节变量矩阵
参数：xlab
<PRE>x</PRE>-axis label, default is the “label” attribute of x
<PRE> X </ PRE>轴标签，默认为“标签”属性x
参数：ylab
<PRE>y</PRE>-axis label, default is the “label” attribute of y
<PRE> </ PRE>轴标签，默认为“标签”属性y
参数：ylim
<PRE>y</PRE>-axis limits for logit or log hazard
<PRE> </ PRE>轴限制Logit或log的危险
参数：plim
<PRE>y</PRE>-axis limits for probability scale
<PRE> </ PRE>轴的概率规模的限制
参数：plotcl
plot confidence limits
图的置信区间
参数：showknots
show knot locations with arrows
显示结带箭头的位置
参数：add
add this plot to an already existing plot
这个图添加到一个已经存在的图
参数：subset
subset of observations to process, e.g. sex == "male"
的观测值的子集的过程，例如sex == "male"
参数：lty
line type for plotting estimated spline function
估计样条函数绘制的线路类型
参数：noprint
suppress printing regression coefficients and standard errors
不打印的回归系数和标准误差
参数：m
for model="logistic", plot grouped estimates with triangles. Each group contains m ordered observations on x.
为model="logistic"，图分组三角形的估计。每个组都包含m下令观察x，。
参数：smooth
plot nonparametric estimate if model="logistic" and adj is not specified
图非参数估计，如果model="logistic"和adj不指定
参数：bass
smoothing parameter (see supsmu)
平滑参数（见supsmu）
参数：main
main title, default is "Estimated Spline Transformation"
主标题，默认情况下是"Estimated Spline Transformation"
参数：statloc
location of summary statistics. Default positioning by clicking left mouse button where upper left corner of statistics should appear. Alternative is "ll" to place below the graph on the lower left, or the actual x and y coordinates. Use "none" to suppress statistics.
位置的汇总统计。默认定位，通过点击鼠标左键应该出现在左上角的统计。另一种方法是"ll"将下面的图的左下角，或实际的x和y坐标。使用"none"抑制统计。
值----------Value----------
list with components (knots, x, xbeta, lower, upper) which are respectively the knot locations, design matrix, linear predictor, and lower and upper confidence limits
名单分别结位置，设计矩阵，线性预测，并降低与的组件（knots，x，xbeta，lower，upper）上的置信区间
（作者）----------Author(s)----------
Frank Harrell <br>
Department of Biostatistics, Vanderbilt University <br>
<a href="mailto:f.harrell@vanderbilt.edu">f.harrell@vanderbilt.edu</a>
参见----------See Also----------
lrm, cph, rcspline.eval, plot, supsmu, coxph.fit, lrm.fit
lrm，cph，rcspline.eval，plot，supsmu，coxph.fit，lrm.fit
实例----------Examples----------
#rcspline.plot(cad.dur, tvdlm, m=150)[rcspline.plot（cad.dur，tvdlm，M = 150）]
#rcspline.plot(log10(cad.dur+1), tvdlm, m=150)[rcspline.plot（LOG10（cad.dur +1），tvdlm的，M = 150）]
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。
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发表于 2012-9-20 22:31:37
