weight_estimator_BLH_noprior(RCASPAR)
weight_estimator_BLH_noprior()所属R语言包：RCASPAR
Returns the value of the objective function used for optimizing for the regression parameters and baseline hazards in the model, without including the prior on the regression coefficients.
返回的优化模型回归参数和基线危险，不包括回归系数前，所使用的目标函数值。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Given the arguments, it can evaluate the value of the objective function used by the optimization algorithms for determining the optimal regression parameters and baseline hazard values without including the prior on the regression coefficients, which can be necessary if the starting conditions are set to the origin, which is very peaked in case of inclusion of the prior distribution.
鉴于参数，它可以评估目标函数值的优化算法用于确定最优回归参数和基线危险值，不包括前回归系数，它可以是必要的，如果条件设置为原点，这是非常尖锐的在列入先验分布的情况下。
用法----------Usage----------
weight_estimator_BLH_noprior(geDataT, survDataT, weights_baselineH, a, b, groups)
参数----------Arguments----------
参数：survDataT
The survival data of the patient set passed on by the user. It takes on the form of a data frame with 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”.
患者组的生存数据传给用户。它需要一个数据框的形式，至少有下列列“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：geDataT
The co-variate data (gene expression or aCGH, etc...) of the patient set passed on by the user. It is a matrix with the co-variates in the columns and the subjects in the rows. Each cell corresponds to that rowth subject's columnth co-variate's value.
病人组（基因表达或aCGH等）的共同变量的数据传给用户。这是一个矩阵与合作中的列和行的科目的变元。每个单元格对应，该rowth题目的columnth的共同变量的值。
参数：weights_baselineH
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：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。
值----------Value----------
A vector of the same length as the "weights_baselineH" argument corresponding to the calculated derivatives of the objective with respect to every component of "weights_baselineH".
一个对应与尊重每一个组件的“weights_baselineH”的目标计算的衍生工具为“weights_baselineH”的说法相同长度的向量。
注意----------Note----------
This function is in itself not useful to the user, but is used within the function weights.BLH
这个功能本身并不是对用户有用的，但在功能weights.BLH
作者（S）----------Author(s)----------
Douaa Mugahid
参考文献----------References----------
of Statistics, 34(2), 187-220. The extension of the Cox model to its stepwise form was adapted from: Ibrahim, J.G, Chen, M.-H. & Sinha, D. (2005). Bayesian Survival Analysis (second ed.). NY: Springer. as well as Kaderali, Lars.(2006) A Hierarchial Bayesian Approach to Regression and its Application to Predicting Survival Times in Cancer Patients. Aachen: Shaker
参见----------See Also----------
weight_estimator_BLH, deriv_weight_estimator_BLH_noprior
weight_estimator_BLH，deriv_weight_estimator_BLH_noprior
举例----------Examples----------
data(Bergamaschi)
data(survData)
weight_estimator_BLH_noprior(geDataT=Bergamaschi[1:10, 1:2], survDataT=survData[1:10, 9:10], weights_baselineH=c(0.1,0.2,0.3,rep(0,2)), a=1.5, b=0.3, groups=3)
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 12:08:48
