reduced.sample(spatstat)
reduced.sample()所属R语言包：spatstat
Reduced Sample Estimator using Histogram Data
减少样本估计使用直方图数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute the Reduced Sample estimator of a survival time distribution function, from histogram data
从直方图数据计算减少样品的生存时间分布函数的估计，
用法----------Usage----------
reduced.sample(nco, cen, ncc, show=FALSE, uppercen=0)
参数----------Arguments----------
参数：nco
vector of counts giving the histogram of uncensored observations (those survival times that are less than or equal to the censoring time)
矢量给直方图未经审查的观测（那些存活时间是小于或等于的审查时间的计数）
参数：cen
vector of counts giving the histogram of censoring times
向量计数的直方图的审查
参数：ncc
vector of counts giving the histogram of censoring times for the uncensored observations only
向量计数给直方图的审查，未经审查的意见
参数：uppercen
number of censoring times greater than the rightmost histogram breakpoint (if there are any)
审查倍大于最右边的直方图断点的数目（如果有任何）
参数：show
Logical value controlling the amount of detail returned by the function value (see below)
控制量的详细返回逻辑值的函数值（见下文）
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 reduced sample estimator from a huge dataset.
主要用于内部使用在spatstat此功能是需要的，但在要在其中形成减少样本估计器，从一个巨大的数据集的其他应用程序可能是有用的。
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。
If the number of observations M is large, it is efficient to use histograms. Form the histogram cen of all censoring times C[i]. That is, obs[k] counts the number of values C[i] in the interval (breaks[k],breaks[k+1]] for k > 1 and [breaks[1],breaks[2]] for k = 1. Also form the histogram nco of all uncensored times, i.e. those T*[i] such that D[i]=1, and the histogram of all censoring times for which the survival time is uncensored, i.e. those C[i] such that D[i]=1. These three histograms are the arguments passed to kaplan.meier.
如果该号码的观察M是大的，它是有效利用直方图。形成直方图cen的所有审查时间C[i]。也就是说，obs[k]计值的数量C[i]在区间(breaks[k],breaks[k+1]]的k > 1和[breaks[1],breaks[2]]k = 1。同时形成的直方图nco所有未经审查的时间，即T*[i]等D[i]=1“和直方图的审查赖以生存时间是未经审查的，即这些C[i] 等D[i]=1。这三个直方图的参数传递给kaplan.meier。
The return value rs is the reduced-sample estimator of the distribution function F(t). Specifically, rs[k] is the reduced sample estimate of F(breaks[k+1]). The value is exact, i.e. the use of histograms does not introduce any approximation error.
返回值rs是减少样本的分布函数F(t)估计。具体来说，rs[k]是减少抽样估计的F(breaks[k+1])。该值是确切的，即使用直方图不会引入任何近似误差。
Note that, for the results to be valid, either the histogram breaks must span the censoring times, or the number of censoring times that do not fall in a histogram cell must have been counted in uppercen.
需要注意的是，结果是有效的，无论是在直方图截断必须跨越的审查，或审查，不属于在直方图中单元的数量必须已计算在uppercen。
值----------Value----------
If show = FALSE, a numeric vector giving the values of the reduced sample estimator. If show=TRUE, a list with three components which are vectors of equal length,
如果show = FALSE，一个数字矢量，减少样本估计值。如果show=TRUE，具有三个分量，是矢量长度相等，一个列表
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：numerator
numerator of the reduced sample estimator
的降低了的采样估计的分子
参数：denominator
denominator of the reduced sample estimator
分母的降低了的采样估计
（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----------
kaplan.meier, km.rs
kaplan.meier，km.rs
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 14:04:43
