default.saemix.plots(saemix)
default.saemix.plots()所属R语言包：saemix
Wrapper functions to produce certain sets of default plots
包装功能产生一定的预设绘图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
These functions produce default sets of plots, corresponding to diagnostic or individual fits.
这些功能产生默认的套图，相应的诊断或个人一刀切。
用法----------Usage----------
default.saemix.plots(saemixObject, ...)
basic.gof(saemixObject, ...)
advanced.gof(saemixObject, ...)
covariate.fits(saemixObject, which = "parameters", ...)
individual.fits(saemixObject, ...)
参数----------Arguments----------
参数：saemixObject
an object returned by the saemix function
返回的对象saemix的函数
参数：which
for covariate fits, whether they should be produced with the EBE estimates of the parameters (the default) or with random effects (which="randeff")
为协千篇一律，是否应该EBE估计的参数（默认值）或随机效应（=“randeff”）
参数：...
optional arguments passed to the plots
可选参数传递给该图
Details
详细信息----------Details----------
These functions are wrapper functions designed to produce default sets of plots to help the user assess their model fits.
这些功能的包装设计，生产图的默认组，以帮助用户评估其模型拟合功能。
值----------Value----------
<table summary="R valueblock"> <tr valign="top"><td>default.saemix.plots</td> <td> by default, the following plots are produced: a plot of the data, convergence plots, plot of the likelihood by importance sampling (if computed), plots of observations versus predictions, scatterplots and distribution of residuals, boxplot of the random effects, correlations between random effects, distribution of the parameters, VPC</td></tr> <tr valign="top"><td>basic.gof</td> <td> basic goodness-of-fit plots: convergence plots, plot of the likelihood by importance sampling (if computed), plots of observations versus predictions</td></tr> <tr valign="top"><td>advanced.gof</td> <td> advanced goodness-of-fit plots: scatterplots and distribution of residuals, VPC,...</td></tr> <tr valign="top"><td>covariate.fits</td> <td> plots of all estimated parameters versus all covariates in the dataset</td></tr> <tr valign="top"><td>individual.fits</td> <td> plots of individual predictions (line) overlayed on individual observations (dots) for all subjects in the dataset</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD> default.saemix.plots</ TD> <TD>默认情况下，下面的图是：一个图的数据，收敛图，重要性抽样的可能性（如果计算）的图，图的观测与预测，散点图和残差分布，盒形图的随机效应，随机效应，分布参数之间的相关性，VPC </ TD> </ TR> < TR VALIGN =“”> <TD> basic.gof </ TD> <TD>基本的善良的拟合图：收敛图，图的可能性重要性抽样（如果计算），图的观察与预测</ TD> </ TR> <tr valign="top"> <TD> advanced.gof </ TD> <TD>先进的善良的拟合图：散点图和分布的残留物，VPC，... </ TD> </ TR> <tr valign="top"> <TD>covariate.fits </ TD> <TD>图的所有估计参数与所有协变量的数据集</ TD> </ TR> <tr valign="top"> <TD> individual.fits </ TD> <TD>个人的预测（行）个人意见（点）覆盖在所有科目中的数据集</ TD> </ TR图> </ TABLE>
（作者）----------Author(s)----------
Emmanuelle Comets <emmanuelle.comets@inserm.fr>, Audrey Lavenu, Marc Lavielle.
参考文献----------References----------
Monolix32_UsersGuide.pdf (http://software.monolix.org/sdoms/software/)
参见----------See Also----------
saemix, saemix.plot.data, saemix.plot.setoptions, plot.saemix
saemix，saemix.plot.data，saemix.plot.setoptions，plot.saemix
实例----------Examples----------
data(theo.saemix)
saemix.data<-saemixData(name.data=theo.saemix,header=TRUE,sep=" ",na=NA,
name.group=c("Id"),name.predictors=c("Dose","Time"),
name.response=c("Concentration"),name.covariates=c("Weight","Sex"),
units=list(x="hr",y="mg/L",covariates=c("kg","-")), name.X="Time")
model1cpt<-function(psi,id,xidep) {
dose<-xidep[,1]
tim<-xidep[,2]
ka<-psi[id,1]
V<-psi[id,2]
CL<-psi[id,3]
k<-CL/V
ypred<-dose*ka/(V*(ka-k))*(exp(-k*tim)-exp(-ka*tim))
return(ypred)
}
saemix.model<-saemixModel(model=model1cpt,
description="One-compartment model with first-order absorption",
psi0=matrix(c(1.,20,0.5,0.1,0,-0.01),ncol=3, byrow=TRUE,
dimnames=list(NULL, c("ka","V","CL"))),transform.par=c(1,1,1),
covariate.model=matrix(c(0,1,0,0,0,0),ncol=3,byrow=TRUE),fixed.estim=c(1,1,1),
covariance.model=matrix(c(1,0,0,0,1,0,0,0,1),ncol=3,byrow=TRUE),
omega.init=matrix(c(1,0,0,0,1,0,0,0,1),ncol=3,byrow=TRUE),error.model="constant")
saemix.options<-list(seed=632545,save=FALSE,save.graphs=FALSE)
saemix.fit<-saemix(saemix.model,saemix.data,saemix.options)
default.saemix.plots(saemix.fit)
basic.gof(saemix.fit)
advanced.gof(saemix.fit)
individual.fits(saemix.fit)
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 21:24:30
