fitmle(scaRabee)
fitmle()所属R语言包：scaRabee
Maximum Likelihood Estimator
最大似然估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
fitmle is a secondary function called during estimation runs. It performs the optimization of the model parameters by the method of the maximum likelihood, i.e. the minimization of an objective function defined as the exact negative log likelihood of the observed data, given the structural model, the model of residual variability, and the parameter estimates. This minimization is performed by the Nelder-Mead simplex algorithm implemented in fminsearch from the neldermead package. fitmle is typically not called directly by users.
fitmle是一个二次函数调用在估算过程中运行。它执行的优化的模型参数的最大似然方法，即定义为所观察到的数据的精确的负对数似然的目标函数的最小化，给定的结构模型，该模型的残余变异，和参数估计。这种最小化的内尔德-Mead单纯形算法的实现在fminsearchneldermead包。 fitmle通常不直接调用用户。
用法----------Usage----------
fitmle(problem = NULL,
estim.options = 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 containing as many levels as there are treatment levels for the subject (or population) being evaluated, plus the trts level listing all treatments for this subject (or population), and the id level giving the identification number of the subject (or set to 1 if the analysis was run at the level of the population. Each treatment-specific level is a list containing the following levels:
DATAA列表含有作为多层次的，有被评估为主体的处理水平（或人群），加上trts级以上市对这个问题的所有处理（或人群），而id水平给予被检体的识别号码（或设置为1，如果分析在人口水平运行。每个治疗特定的电平是一个列表，其中包含以下级别：
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.
覆盖MIJ×3数据框的类型相关的变量（CMT变量提取），而实际的因变量的观测指标（含观测到的因变量（从时间变量中提取）的时代，提取的变量）的DV为这个特定的处理。
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.
covmij XC数据框包含时间的观察因变量（从时间变量中提取）和所有的协变量确定这个特殊的处理。
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：estim.options
A list of estimation options containing two elements maxiter (the maximum number of iterations) and maxeval (the maximum number of function evaluations).
估计选项的列表包含两个元素maxiter（迭代的最大数量）和maxeval（功能评价的最大数目）。
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）。
值----------Value----------
Return a list with two elements: estimations which contains the vector of final parameter estimates and fval the minimal value of the objective function.
返回一个列表有两个元素：estimations包含矢量的最后一个参数的估计和fval的目标函数的最小值。
（作者）----------Author(s)----------
Sebastien Bihorel (<a href="mailto:sb.pmlab@gmail.com">sb.pmlab@gmail.com</a>)
Pawel Wiczling
参见----------See Also----------
fminsearch
fminsearch
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。
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发表于 2012-9-29 22:45:32
