validate.Rq(rms)
validate.Rq()所属R语言包：rms
Validation of a Quantile Regression Model
一个位数回归模型的验证
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The validate function when used on an object created by Rq does resampling validation of a quantile regression model, with or without backward step-down variable deletion. Uses resampling to estimate the optimism in various measures of predictive accuracy which include mean absolute prediction error (MAD), Spearman rho, the g-index, and the intercept and slope of an overall calibration a + b * (predicted y). The "corrected" slope can be thought of as shrinkage factor that takes into account overfitting. validate.Rq can also be used when a model for a continuous response is going to be applied to a binary response. A Somers' D_{xy} for this case is computed for each resample by dichotomizing y. This can be used to obtain an ordinary receiver operating characteristic curve area using the formula 0.5(D_{xy} + 1). See predab.resample for the list of resampling methods.
validate功能使用时，Rq不重采样的位数回归模型的验证，带或不带倒退的变数删除创建的对象。使用在各种措施的预测精度，其中包括平均绝对预测误差（MAD），斯皮尔曼RHO，g指数，和截距和斜率的整体校准a + b * (predicted y)重采样的乐观估计。 “修正”的斜率可以被认为是收缩的因素，需要考虑过拟合。 validate.Rq时，也可用于连续反应的模型为将要被施加到一个二进制响应。一个萨默斯D_{xy}这种情况下，计算每个重采样的二分法y。这可以被用来获得一个普通的接收机工作特性曲线下面积，使用式0.5(D_{xy} + 1)。 predab.resample的重采样方法的列表。
The LaTeX needspace package must be in effect to use the latex method.
必须在效果LaTeX的needspace包，使用latex方法。
用法----------Usage----------
# fit <- fitting.function(formula=response ~ terms, x=TRUE, y=TRUE)
## S3 method for class 'Rq'
validate(fit, method="boot", B=40,
bw=FALSE, rule="aic", type="residual", sls=0.05, aics=0,
force=NULL, pr=FALSE, u=NULL, rel=">", tolerance=1e-7, ...)
参数----------Arguments----------
参数：fit
a fit derived by Rq. The options x=TRUE and y=TRUE must have been specified. See validate for a description of arguments method - pr.
适合取得的Rq。的选项x=TRUE和y=TRUE必须被指定。见validate参数的描述method - pr。
参数：method,B,bw,rule,type,sls,aics,force,pr
see validate and predab.resample and fastbw
看到validate和predab.resample和fastbw
参数：u
If specifed, y is also dichotomized at the cutoff u for the purpose of getting a bias-corrected estimate of D_{xy}.
如果具体确定，y还二在截止u为目的，得到一个修正偏置估计D_{xy}。
参数：rel
relationship for dichotomizing predicted y. Defaults to ">" to use y>u. rel can also be "<", ">=", and "<=".
关系，二分法预测y。默认为">"使用y>u。 rel也可以"<"，">="和"<="。
参数：tolerance
ignored
忽视
参数：...
other arguments to pass to predab.resample, such as group, cluster, and subset </table>
其他参数传递给predab.resample，如group，cluster和subset </表>
值----------Value----------
matrix with rows corresponding to various indexes, and optionally D_{xy}, and columns for the original index, resample estimates, indexes applied to whole or omitted sample using model derived from resample, average optimism, corrected index, and number of successful resamples.
矩阵的行对应的各项指标，并选择性地D_{xy}，并纠正原来的索引列，重采样适用于全部或省略的样品模型来自重采样，平均乐观的估计，索引，索引，和一些成功的重采样。
副作用----------Side Effects----------
prints a summary, and optionally statistics for each re-fit
为每一个再适合打印的总结，并选择性地统计
（作者）----------Author(s)----------
Frank Harrell<br>
Department of Biostatistics, Vanderbilt University<br>
f.harrell@vanderbilt.edu
参见----------See Also----------
Rq, predab.resample, fastbw, rms, rms.trans, gIndex
Rq，predab.resample，fastbw，rms，rms.trans，gIndex
实例----------Examples----------
set.seed(1)
x1 <- runif(200)
x2 <- sample(0:3, 200, TRUE)
x3 <- rnorm(200)
distance <- (x1 + x2/3 + rnorm(200))^2
f <- Rq(sqrt(distance) ~ rcs(x1,4) + scored(x2) + x3, x=TRUE, y=TRUE)
#Validate full model fit (from all observations) but for x1 < .75[验证完整的模型拟合（从所有观测），但对于x1 <0.75]
validate(f, B=20, subset=x1 < .75) # normally B=150[通常B = 150]
#Validate stepwise model with typical (not so good) stopping rule[验证逐步模型与典型的（不太好）停止规则]
validate(f, B=20, bw=TRUE, rule="p", sls=.1, type="individual")
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 2012-9-27 19:18:01
