estimation.plot(scaRabee)
estimation.plot()所属R语言包：scaRabee
Create Summary Estimation Plots
创建摘要估计图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
estimation.plot is a secondary function called at the end of the estimation runs. It generates plots from the iteration log file and the prediction & residual file. Those plots are: a figure summarizing the changes in the objective function and the estimated parameter values as a function of the iteration plus, for each subject and sub-problem (i.e. treatment), a figure overlaying model predictions and observed data, and another figure showing 4 goodness-of-fit plots (predictions vs observations, weighted residuals vs time, weighted residuals vs observations, weighted residuals vs predictions). See vignette('scaRabee',package='scaRabee') for more details. estimation.plot is typically not called directly by users.
estimation.plot是在结束的估计运行的二次函数调用。它可以生成图的迭代log文件，并预测剩余的文件。这些图是：一个数字总结在目标函数中，作为迭代的函数的估计的参数值的变化，则加上每个主体和子问题（即处理），一个数字的重叠的模型预测和观察到的数据，和另一个数字显示4个善良的拟合图（预测与观察，加权残值法与时间，加权残值法与观察，加权残值法与预测）。见vignette('scaRabee',package='scaRabee')更多详情。 estimation.plot通常不直接调用用户。
用法----------Usage----------
estimation.plot(problem = NULL,
Fit = NULL,
files = NULL)
参数----------Arguments----------
参数：problem
A list containing the following levels:
一个列表，其中包含以下几个层次：
dataA list which content depends on the scope of the analysis. If the analysis was run at the level of the subject, data contains as many levels as the number of subjects in the dataset, plus the ids level containing the vector of identification numbers of all subjects included in the analysis population. If the analysis was run at the level of the population, data contains only one level of data and ids is set to 1. Each subject-specific level contains as many levels as there are treatment levels for this subject, plus the trts level listing all treatments for this subject, and the id level giving the identification number of the subject. Each treatment-specific levels is a list containing the following levels:
DATAA列表的内容取决于分析的范围。如果分析被运行在被检体的水平，data中的数据集的数量的受试者包含尽可能多的水平，加上ids水平含有向量的所有主题的识别号码包含在分析人口。如果分析在人口水平运行，data只包含一个电平的数据和ids被设置为1。每个特定主题的多层次，有对这个问题的处理水平，加上trts级以上市对这个问题的所有治疗，和id水平的标识号的主题。每一个具体的治疗水平是一个列表，其中包含以下几个层次：
cov mij x 3 data.frame containing the times of observations of the dependent variables (extracted from the TIME variable), the indicators of the type of dependent variables (extracted from the CMT variable), and the actual dependent variable observations (extracted from the DV variable) for this particular treatment and this particular subject.
covmij x c data.frame containing the times of observations of the dependent variables (extracted from the TIME variable) and all the covariates identified for this particular treatment and this particular subject.
covmij XC数据框包含因变量（从时间变量中提取）和这个特殊的治疗和这个特定的主题确定为所有的协变量的观测时间。
bolusbij x 4 data.frame providing the instantaneous inputs for a treatment and individual.
bolusbij×4的数据框提供的治疗和个人的瞬时输入。
infusionfij x (4+c) data.frame providing the zero-order inputs for a treatment and individual.
infusionfij×（4 + c的）数据框提供零阶的输入处理和个人。
trtthe particular treatment identifier.
trtthe特别治疗标识符。
methodA character string, indicating the scale of the analysis. Should be 'population' or 'subject'.
了methodA字符串，表示规模的分析。应该是“人口”或“主题”。
initA data.frame of parameter data with the following columns: 'names', 'type', 'value', 'isfix', 'lb', and 'ub'.
INITA数据框的参数数据有以下几列：名称，类型，价值，isfix，磅，和UB。
debugmodeLogical indicator of debugging mode.
除错模式的debugmodeLogical指标。
modfunModel function.
modfunModel功能。
参数：Fit
A list containing the following elements:
一个列表，其中包含以下元素：
estimationsThe vector of final parameter estimates.
estimationsThe向量的最后一个参数估计。
fvalThe minimal value of the objective function.
fvalThe的目标函数的值最小。
covThe matrix of covariance for the parameter estimates.
covThe的参数协方差矩阵的估计。
orderedestimationsA data.frame with the same structure as problem$init but only containing the sorted estimated estimates. The sorting is performed by order.param.list.
orderedestimationsA数据框具有相同的结构problem$init但仅包含排序条件估计的估计。排序是由order.param.list。
corThe upper triangle of the correlation matrix for the parameter estimates.
corThe的相关矩阵的上三角的参数估计。
cvThe coefficients of variations for the parameter estimates.
cvThe系数为参数估计的变化。
ciThe confidence interval for the parameter estimates.
ciThe的参数的置信区间估计。
AICThe Akaike Information Criterion.
AICThe赤池信息准则。
secA list of data related to the secondary parameters, containing the following elements:
SECA二次参数有关的数据列表，包含以下元素：
estimates The vector of secondary parameter estimates calculated using the initial estimates of the primary model parameters.
估计矢量副参数估计来计算的主要模型参数的初步估计。
namesThe vector of names of the secondary parameter estimates.
namesThe向量的二次参数估计的名称。
pderThe matrix of partial derivatives for the secondary parameter estimates.
pderThe矩阵的偏导数为辅助参数估计。
covThe matrix of covariance for the secondary parameter estimates.
covThe协方差矩阵的为副参数估计。
cvThe coefficients of variations for the secondary parameter estimates.
cvThe系数的为副参数估计的变化。
ciThe confidence interval for the secondary parameter estimates.
ciThe副参数估计值的置信区间。
orderedfixedA data.frame with the same structure as problem$init but only containing the sorted fixed estimates. The sorting is performed by order.param.list.
orderedfixedA数据框具有相同的结构problem$init但仅包含排序条件固定的估计。排序是由order.param.list。
orderedinitialA data.frame with the same content as problem$init but sorted by order.param.list.
orderedinitialA数据框相同的内容problem$init但排序由order.param.list。
参数：files
A list of input used for the analysis. The following elements are expected and none of them could be null:
用于分析的输入的列表。预计下列元素和他们没有可能为空：
dataA .csv file located in the working directory, which contains the dosing information, the observations of the dependent variable(s) to be modeled, and possibly covariate information. The expected format of this file is described in details in vignette('scaRabee', package='scaRabee').
DATAA。csv文件的工作目录，其中包含的剂量信息，（因变量）的意见进行建模，以及可能的协变量的信息。该文件格式的细节vignette('scaRabee', package='scaRabee')。
paramA .csv file located in the working directory, which contains the initial guess(es) for the model parameter(s) to be optimized or used for model simulation. The expected format of this file is described in details in vignette('scaRabee',package='scaRabee').
帕拉马。csv文件的工作目录，其中包含了最初的猜测（ES）进行优化或用于模型仿真模型参数（S）。该文件格式的细节vignette('scaRabee',package='scaRabee')。
modelA text file located in the working directory, which defines the model. Models specified with explicit, ordinary or delay differential equations are expected to respect a certain syntax and organization detailed in vignette('scaRabee',package='scaRabee').
MODELA工作目录中的文本文件，它定义了模型。指定明确的，普通或延迟微分方程模型应尊重一定的语法和组织中详述vignette('scaRabee',package='scaRabee')。
iterA .csv file reporting the values of the objective function and estimates of model parameters at each iteration.
迭代。csv文件报告在每次迭代的目标函数和模型参数的估计值。
reportA text file reporting for each individual in the dataset the final parameter estimates for structural model parameters, residual variability and secondary parameters as well as the related statistics (coefficients of variation, confidence intervals, covariance and correlation matrix).
reportA文本文件报告为每个数据集的结构模型参数，剩余的可变性和次要参数以及相关的统计数据（系数的变化，置信区间，协方差和相关矩阵）的最后一个参数估计。
predA .csv file reporting the predictions and calculated residuals for each individual in the dataset.
报告的预测和计算残差的每一个人在该数据集的捕食者。csv文件。
estA .csv file reporting the final parameter estimates for each individual in the dataset.
ESTA。csv文件，报告的最后一个参数估计为每个数据集。
simA .csv file reporting the simulated model predictions for each individual in the dataset. (Not used for estimation runs).
司马。csv文件报告为每个数据集模拟模型的预测结果。 （不用于估计运行）。
（作者）----------Author(s)----------
Sebastien Bihorel (<a href="mailto:sb.pmlab@gmail.com">sb.pmlab@gmail.com</a>)
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 2012-9-29 22:44:57
