survreg.distributions(survival)
survreg.distributions()所属R语言包：survival
Parametric Survival Distributions
参数生存分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
List of distributions for accelerated failure models. These are location-scale families for some transformation of time. The entry describes the cdf F and density f of a canonical member of the family.
加速失效模型的分布名单。这些位置一段时间的改造规模的家庭。该条目描述的CDF F密度典型的家庭成员f。
用法----------Usage----------
survreg.distributions
格式----------Format----------
There are two basic formats, the first defines a distribution de novo, the second defines a new distribution in terms of an old one.
有两个基本的格式，首先定义了一个新的分布，第二个定义在一个老的新的分配。
name of distribution
分布名称
function(parms) returning the variance (currently unused)
功能（PARMS）返回的变异（目前未使用）
Function returning an initial
函数返回一个初始
estimate of the mean and variance
均值和方差的估计
(used for initial values in the iteration)
（用于在迭代的初始值）
Function returning a matrix with columns F,
函数返回的列矩阵F，
1-F,f,f'/f,f''/f
1-F，f，f'/f，f''/f
Quantile function
分量函数
Optional fixed value for the scale parameter
为尺度参数的可选固定值
Vector of default values and names for any additional parameters
向量的默认值和任何额外的参数的名称
Function returning the deviance for a
函数返回一个偏差
and to define one distribution in terms of another
定义在另一个方面分布
name of distribution
分布名称
name of parent distribution
母公司的名称分布
transformation (eg log)
变换（如日志）
derivative of transformation
衍生转型
inverse of transformation
逆变换
Optional fixed value for scale parameter
可选的固定价值为尺度参数
Details
详情----------Details----------
There are four basic distributions:extreme, gaussian, logistic and t. The last three are parametrised in the same way as the distributions already present in R. The extreme value cdf is
有四种基本分布：extreme，gaussian，logistic和t。过去三年都在以同样的方式parametrised分布已经呈现在河CDF是极端值
When the logarithm of survival time has one of the first three distributions we obtain respectively weibull, lognormal, and loglogistic. The location-scale parameterizaion of a Weibull distribution found in survreg is not the same as the parameterization of rweibull.
当生存时间的对数前三分布之一，我们分别获得weibull，lognormal，loglogistic。找到了survreg Weibull分布的位置，规模parameterizaion不是rweibull参数相同。
The other predefined distributions are defined in terms of these. The exponential and rayleigh distributions are Weibull distributions with fixed scale of 1 and 0.5 respectively, and loggaussian is a synonym for lognormal.
其他预定义分布在这些条款的定义。 exponential和rayleigh分布与威布尔分布固定scale分别为1和0.5，loggaussian是lognormal的代名词。
For speed parts of the three most commonly used distributions are hardcoded in C; for this reason the elements of survreg.distributions with names of "Extreme value", "Logisitic" and "Gaussian" should not be modified. (The order of these in the list is not important, recognition is by name.) As an alternative to modifying survreg.distributions a new distribution can be specified as a separate list. This is the preferred method of addition and is illustrated below.
对于最常用的三个发行速度部分是硬编码在C中的元素，为这个原因survreg.distributions“极值”，“Logisitic”和“高斯”的名称不应该被修改。 （这些列表中的顺序并不重要，承认的名字。）作为替代来修改survreg.distributions可以作为一个单独的列表中指定一个新的分布。这是加法的首选方法，如下所示。
参见----------See Also----------
survreg, pweibull, pnorm,plogis, pt, survregDtest
survreg，pweibull，pnorm，plogis，pt，survregDtest
举例----------Examples----------
# time transformation[时间转换]
survreg(Surv(time, status) ~ ph.ecog + sex, dist='weibull', data=lung)
# change the transformation to work in years[改变工作多年的改造]
# intercept changes by log(365), everything else stays the same[拦截日志（365）的变化，一切保持不变]
my.weibull <- survreg.distributions$weibull
my.weibull$trans <- function(y) log(y/365)
my.weibull$itrans <- function(y) 365*exp(y)
survreg(Surv(time, status) ~ ph.ecog + sex, lung, dist=my.weibull)
# Weibull parametrisation[威布尔parametrisation]
y<-rweibull(1000, shape=2, scale=5)
survreg(Surv(y)~1, dist="weibull")
# survreg parameters are scale=1/shape, intercept=log(scale)[survreg参数是规模= 1/shape，拦截日志（规模）]
# Cauchy fit[柯西适合]
mycauchy <- list(name='Cauchy',
init= function(x, weights, ...)
c(median(x), mad(x)),
density= function(x, parms) {
temp <- 1/(1 + x^2)
cbind(.5 + atan(x)/pi, .5+ atan(-x)/pi,
temp/pi, -2 *x*temp, 2*temp*(4*x^2*temp -1))
},
quantile= function(p, parms) tan((p-.5)*pi),
deviance= function(...) stop('deviance residuals not defined')
)
survreg(Surv(log(time), status) ~ ph.ecog + sex, lung, dist=mycauchy)
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 20:55:56
