km.rs(spatstat)
km.rs()所属R语言包：spatstat
Kaplan-Meier and Reduced Sample Estimator using Histograms
Kaplan-Meier和减少样本估计使用直方图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute the Kaplan-Meier and Reduced Sample estimators of a survival time distribution function, using histogram techniques
Kaplan-Meier法计算，减少样品的生存时间分布函数的估计，使用直方图技术
用法----------Usage----------
km.rs(o, cc, d, breaks)
参数----------Arguments----------
参数：o
vector of observed survival times
矢量观测到的存活时间
参数：cc
vector of censoring times
矢量的审查
参数：d
vector of non-censoring indicators
向量的非审查指标
参数：breaks
Vector of breakpoints to be used to form histograms.
向量被用于形成直方图的断点。
Details
详细信息----------Details----------
This function is needed mainly for internal use in spatstat, but may be useful in other applications where you want to form the Kaplan-Meier estimator from a huge dataset.
此功能主要用于需要内部使用中spatstat的，但在其他的应用中，你想从一个巨大的数据集形成的Kaplan-Meier估计可能是有用的。
Suppose T[i] are the survival times of individuals i=1,…,M with unknown distribution function F(t) which we wish to estimate. Suppose these times are right-censored by random censoring times C[i]. Thus the observations consist of right-censored survival times T*[i] = min(T[i],C[i]) and non-censoring indicators D[i] = 1(T[i] <= C[i]) for each i.
假设T[i]是个人的存活时间i=1,…,M未知分布的功能F(t)我们希望估计。假设这些时间右删失随机审查倍C[i]。因此，观察由右删失的生存时间T*[i] = min(T[i],C[i])和非设限指标D[i] = 1(T[i] <= C[i])每个i。
The arguments to this function are vectors o, cc, d of observed values of T*[i], C[i] and D[i] respectively. The function computes histograms and forms the reduced-sample and Kaplan-Meier estimates of F(t) by invoking the functions kaplan.meier and reduced.sample. This is efficient if the lengths of o, cc, d (i.e. the number of observations) is large.
到该函数的参数向量o，cc，dT*[i]，C[i]和D[i]分别观测值。该函数计算直方图和形成减少样品和Kaplan-Meier估计F(t)通过调用功能kaplan.meier和reduced.sample，。这是有效的，如果长度o，cc，d（即若干意见）大。
The vectors km and hazard returned by kaplan.meier are (histogram approximations to) the Kaplan-Meier estimator of F(t) and its hazard rate lambda(t). Specifically, km[k] is an estimate of F(breaks[k+1]), and lambda[k] is an estimate of the average of lambda(t) over the interval (breaks[k],breaks[k+1]). This approximation is exact only if the survival times are discrete and the histogram breaks are fine enough to ensure that each interval (breaks[k],breaks[k+1]) contains only one possible value of the survival time.
的矢量km和hazard返回kaplan.meier（直方图近似）的Kaplan-Meier估计F(t)和它的危险率lambda(t)。具体来说，km[k]是估计F(breaks[k+1])，lambda[k]是一个估计的平均lambda(t)在区间(breaks[k],breaks[k+1])。这种近似是精确的，只有当生存时间是离散的和的直方图的场所是足够细，以确保，每个间隔(breaks[k],breaks[k+1])只包含一个可能的值中的生存时间。
The vector rs is the reduced-sample estimator, rs[k] being the reduced sample estimate of F(breaks[k+1]). This value is exact, i.e. the use of histograms does not introduce any approximation error in the reduced-sample estimator.
向量rs是减少样本的估计，rs[k]减少抽样估计的F(breaks[k+1])。这个值是准确的，即使用直方图并没有引入任何近似误差减少样本估计。
值----------Value----------
A list with five elements
五行列表
参数：rs
Reduced-sample estimate of the survival time c.d.f. F(t)
减少抽样估计的存活时间CDF F(t)
参数：km
Kaplan-Meier estimate of the survival time c.d.f. F(t)
Kaplan-Meier估计的存活时间c.d.f. F(t)
参数：hazard
corresponding Nelson-Aalen estimate of the hazard rate lambda(t)
相应的纳尔逊 - 阿伦估计的危险率lambda(t)
参数：r
values of t for which F(t) is estimated
t值F(t)估计
参数：breaks
the breakpoints vector
断点矢量
（作者）----------Author(s)----------
Adrian Baddeley
<a href="mailto:Adrian.Baddeley@csiro.au">Adrian.Baddeley@csiro.au</a>
<a href="http://www.maths.uwa.edu.au/~adrian/">http://www.maths.uwa.edu.au/~adrian/</a>
and Rolf Turner
<a href="mailto:r.turner@auckland.ac.nz">r.turner@auckland.ac.nz</a>
参见----------See Also----------
reduced.sample, kaplan.meier
reduced.sample，kaplan.meier
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 13:39:54
