weights_BLH(RCASPAR)
weights_BLH()所属R语言包：RCASPAR
Optimization for the regression coefficients and baseline hazards that maximize the partial likelihood in our PW Cox PH regression model.
优化的回归系数和基线的危害，最大限度地提高我们的PW考克斯PH值回归模型的局部可能性。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function is a wrapper around the optimization function optim to allow the optimization for the regression coefficients and baseline hazards appropriate for the data set at hand. It is where the functions weight_estimator_BLH, weight_estimator_BLH_noprior, deriv_weight_estimator_BLH, deriv_weight_estimator_BLH_noprior are required.
此功能是围绕优化功能的包装optim允许优化适合于手头的数据的回归系数和基线危险。它是功能weight_estimator_BLH, weight_estimator_BLH_noprior, deriv_weight_estimator_BLH, deriv_weight_estimator_BLH_noprior需要。
用法----------Usage----------
weights_BLH(geDataT, survDataT, q, s, a, b, groups, par, method = c("Nelder-Mead", "L-BFGS-B", "CG", "BFGS", "SANN"), noprior = 1, extras = list(),
dist = NULL)
参数----------Arguments----------
参数：geDataT
A matrix with the co-variate in the columns and the subjects in the rows.Each cell corresponds to that rowth subject's columnth co-variate's value.
与合作，在列和在rows.Each单元的科目变量的矩阵对应，该rowth题目的columnth的共同变量的值。
参数：survDataT
A data frame with the survival data of the set of subjects at hand. It should at least have the following columns “True_STs” and “censored”, corresponding to the observed survival times and the censoring status of the subjects consecutively. Censored patients are assigned a “1” while patients who experience an event are assigned “1”.
一套在手的受试者的生存数据的一个数据框。至少应该有以下几列“True_STs”和“审查”，相应的观测到的生存时间和审查的受试者连续状态。截患者被分配了一个“1”，而谁遇到事件的患者被指定为“1”。
参数：q
One of the two parameters on the prior distribution used on the weights (regression coefficients) in the model.
模型中的权重（回归系数）上使用的先验分布的两个参数之一。
参数：s
The second of the two parameters on the prior distribution used on the weights (regression coefficients) in the model.
第二先验分布的两个参数用于模型中的权重（回归系数）。
参数：a
The shape parameter for the gamma distribution used as a prior on the baseline hazards.
作为基线的危害之前使用伽玛分布的形状参数。
参数：b
The scale parameter for the gamma distribution used as a prior on the baseline hazards.
作为基线的危害之前使用伽玛分布的尺度参数。
参数：groups
The number of partitions along the time axis for which a different baseline hazard is to be assigned. This number should be the same as the number of initial values passed for the baseline hazards in the beginning of the “weights_baselineH” argument.
被分配不同的基线危险是沿时间轴的分区数。这个数字应该是通过的“weights_baselineH”的说法开始在基线危害的初始值相同。
参数：par
A single vector with the initial values of the baseline hazards followed by the weights(regression coefficients) for the co-variates.
单矢量与共同变元的权重（回归系数）危害基线的初始值。
参数：method
The preferred optimization method. It can be one of the following: "Nelder-Mead": for the Nelder-Mead simplex algorithm. "L-BFGS-B": for the L-BFGS-B quasi-Newtonian method. "BFGS": for the BFGS quasi-Newtonian method. "CG": for the Conjugate Gradient decent method "SANN": for the simulated annealing algorithm.
首选的优化方法。它可以是下列之一："Nelder-Mead":内尔德Mead单纯算法。 "L-BFGS-B" -bfgs-B的拟牛顿方法。 "BFGS":BFGS拟牛顿方法。 "CG":体面的共轭梯度法"SANN":模拟退火算法。
参数：noprior
An integer indicating the number of iterations to be done without assuming a prior on the regression coefficients.
一个整数，表示迭代次数进行回归系数事先假设。
参数：extras
The extra arguments to passed to the optimization function optim. For further details on them, see the documentation for the optim function.
额外的参数传递给函数的优化OPTIM。对于他们的进一步详情，请参阅为optim功能的文档。
参数：dist
The distribution function to be passed to the optimization algorithm in case of using SANN to generate a new candidate point.
要传递给使用宋双来生成一个新的候选点的情况下优化算法的分布函数。
值----------Value----------
The same value as the optim function. See it's documentation for details.
作为optim功能相同的值。看到它的详细信息的文档。
注意----------Note----------
Note that this function is just a wrapper around the optim function to serve our purpose, and it's main purpose is to be called within the main functions of this package STpredictor_BLH and weights_xvBLH
注意，这个函数仅仅是一个围绕optim函数的包装，为我们的宗旨，它的主要目的是要呼吁内的主要职能这个包STpredictor_BLH和weights_xvBLH
作者（S）----------Author(s)----------
Douaa Mugahid
参考文献----------References----------
举例----------Examples----------
data(Bergamaschi)
data(survData)
weights_BLH(geDataT=Bergamaschi[1:10,1:2], survDataT=survData[1:10, 9:10], q=1, s=1, a=1.56, b=0.17, groups=3, par=c(0.1,0.2,0.3,rep(0,ncol(Bergamaschi))), method = "CG", noprior = 1, extras =
list(reltol=1), dist = NULL)
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 2012-2-26 12:08:21
