residuals.survreg(survival)
residuals.survreg()所属R语言包：survival
Compute Residuals for ‘survreg’ Objects
计算残值为“survreg”对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This is a method for the function residuals for objects inheriting from class survreg.
这是一个residuals类survreg继承对象的函数方法。
用法----------Usage----------
## S3 method for class 'survreg'
residuals(object, type=c("response", "deviance","dfbeta","dfbetas",
"working","ldcase","ldresp","ldshape", "matrix"), rsigma=TRUE,
collapse=FALSE, weighted=FALSE, ...)
参数----------Arguments----------
参数：object
an object inheriting from class survreg.
继承类survreg对象。
参数：type
type of residuals, with choices of "response", "deviance", "dfbeta", "dfbetas", "working", "ldcase", "lsresp", "ldshape", and "matrix". See the LaTeX documentation (survival/doc/survival.ps.gz) for more detail.
类型的残差，"response"，"deviance"，"dfbeta"，"dfbetas"，"working"，"ldcase"，"lsresp"，选择 "ldshape"，"matrix"。看到更详细的LaTeX文档（survival/doc/survival.ps.gz）。
参数：rsigma
include the scale parameters in the variance matrix, when doing computations. (I can think of no good reason not to).
包括方差矩阵的尺度参数时，做计算。 （我认为没有理由不把好）。
参数：collapse
optional vector of subject groups. If given, this must be of the same length as the residuals, and causes the result to be per group residuals.
学科组的可选向量。如果给定的，这必须是相同的长度为残差，导致的结果是每个组残差。
参数：weighted
give weighted residuals? Normally residuals are unweighted. <tr valign="top"><td>...</td>
给予加权残值？通常残差加权。 <tr valign="top"> <TD>...</ TD>
other unused arguments </table>
其他未使用的参数</ TABLE>
值----------Value----------
A vector or matrix of residuals is returned. Response residuals are on the scale of the original data, working residuals are on the scale of the linear predictor, and deviance residuals are on log-likelihood scale. The dfbeta residuals are a matrix, where the ith row gives the approximate change in the coefficients due to the addition of subject i. The dfbetas matrix contains the dfbeta residuals, with each column scaled by the standard deviation of that coefficient.
返回残差向量或矩阵。响应残差对原始数据的规模，工作残差规模的线性预测，偏差残差对数似然规模。 dfbeta残差是一个矩阵，其中第i行给人由于受我的另外的系数近似变化。在dfbetas基质含有dfbeta的残差，每列的缩放系数的标准偏差。
The matrix type produces a matrix based on derivatives of the log-likelihood function. Let L be the log-likelihood, p be the linear predictor X %*% coef, and s be \log(σ). Then the 6 columns of the matrix are L, dL/dp,ddL/(dp dp), dL/ds, ddL/(ds ds) and ddL/(dp ds). Diagnostics based on these quantities are discussed in an article by Escobar and Meeker. The main ones are the likelihood displacement residuals for perturbation of a case weight (ldcase), the response value (ldresp), and the shape.
矩阵式生产为基础的衍生工具对数似然函数矩阵。让L日志的可能性，p线性预测X %*% coef，s是\log(σ)。然后是6列的矩阵L，dL/dp，ddL/(dp dp)，dL/ds，ddL/(ds ds)和ddL/(dp ds)。基于这些数量的诊断埃斯科瓦尔和米克的文章中讨论。主要的是为扰动的可能性位移的情况下，重残差（ldcase），响应值（ldresp），shape。
参考文献----------References----------
Assessing influence in regression analysis with censored data. Biometrics 48, 507-528.
参见----------See Also----------
predict.survreg
predict.survreg
举例----------Examples----------
fit <- survreg(Surv(time,status) ~x, aml)
rr <- residuals(fit, type='matrix')
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 2012-2-16 21:54:25
