xpose.VPC.both | R Documentation |
Xpose Visual Predictive Check (VPC) for both continuous and Below or Above Limit of Quantification (BLQ or ALQ) data.
xpose.VPC.both( vpc.info = "vpc_results.csv", vpctab = dir(pattern = "^vpctab")[1], object = NULL, subset = NULL, main = "Default", main.sub = NULL, inclZeroWRES = FALSE, cont.logy = F, hline = "default", add.args.cont = list(), add.args.cat = list(), ... )
vpc.info |
Name of PSN file to use. File will come from |
vpctab |
Name of vpctab file produced from PsN. |
object |
Xpose data object. |
subset |
Subset of data to look at. |
main |
Title for plot. |
main.sub |
Used for names above each plot when using multiple plots.
Should be a vector, e.g. |
inclZeroWRES |
Include WRES=0 rows in the computations for these plots? |
cont.logy |
Should the continuous plot y-axis be on the log scale? |
hline |
Horizontal line marking the limits of quantification. If they are defined, they must be a vector of values. |
add.args.cont |
Additional arguments to the continuous plot.
|
add.args.cat |
Additional arguments to the categorical plot.
|
... |
Additional arguments to both plots. |
Andrew C. Hooker
xpose.VPC
, xpose.VPC.categorical
.
Other PsN functions:
boot.hist()
,
bootscm.import()
,
npc.coverage()
,
randtest.hist()
,
read.npc.vpc.results()
,
read.vpctab()
,
xpose.VPC.categorical()
,
xpose.VPC()
,
xpose4-package
Other specific functions:
absval.cwres.vs.cov.bw()
,
absval.cwres.vs.pred.by.cov()
,
absval.cwres.vs.pred()
,
absval.iwres.cwres.vs.ipred.pred()
,
absval.iwres.vs.cov.bw()
,
absval.iwres.vs.idv()
,
absval.iwres.vs.ipred.by.cov()
,
absval.iwres.vs.ipred()
,
absval.iwres.vs.pred()
,
absval.wres.vs.cov.bw()
,
absval.wres.vs.idv()
,
absval.wres.vs.pred.by.cov()
,
absval.wres.vs.pred()
,
absval_delta_vs_cov_model_comp
,
addit.gof()
,
autocorr.cwres()
,
autocorr.iwres()
,
autocorr.wres()
,
basic.gof()
,
basic.model.comp()
,
cat.dv.vs.idv.sb()
,
cat.pc()
,
cov.splom()
,
cwres.dist.hist()
,
cwres.dist.qq()
,
cwres.vs.cov()
,
cwres.vs.idv.bw()
,
cwres.vs.idv()
,
cwres.vs.pred.bw()
,
cwres.vs.pred()
,
cwres.wres.vs.idv()
,
cwres.wres.vs.pred()
,
dOFV.vs.cov()
,
dOFV.vs.id()
,
dOFV1.vs.dOFV2()
,
data.checkout()
,
dv.preds.vs.idv()
,
dv.vs.idv()
,
dv.vs.ipred.by.cov()
,
dv.vs.ipred.by.idv()
,
dv.vs.ipred()
,
dv.vs.pred.by.cov()
,
dv.vs.pred.by.idv()
,
dv.vs.pred.ipred()
,
dv.vs.pred()
,
gof()
,
ind.plots.cwres.hist()
,
ind.plots.cwres.qq()
,
ind.plots()
,
ipred.vs.idv()
,
iwres.dist.hist()
,
iwres.dist.qq()
,
iwres.vs.idv()
,
kaplan.plot()
,
par_cov_hist
,
par_cov_qq
,
parm.vs.cov()
,
parm.vs.parm()
,
pred.vs.idv()
,
ranpar.vs.cov()
,
runsum()
,
wres.dist.hist()
,
wres.dist.qq()
,
wres.vs.idv.bw()
,
wres.vs.idv()
,
wres.vs.pred.bw()
,
wres.vs.pred()
,
xpose.VPC.categorical()
,
xpose.VPC()
,
xpose4-package
## Not run: library(xpose4) ## move to the directory where results from PsN ## are found cur.dir <- getwd() setwd(paste(cur.dir,"/vpc_cont_LLOQ/",sep="")) xpose.VPC() xpose.VPC.categorical(censored=T) xpose.VPC.both() xpose.VPC.both(subset="DV>1.75") xpose.VPC.both(add.args.cont=list(ylim=c(0,80))) xpose.VPC.both(add.args.cont = list(ylim = c(0.01, 80)), xlim = c(0, 40), add.args.cat = list(ylim = c(0, 0.4)), cont.logy = T) xpose.VPC.both(cont.logy=T) ## End(Not run)
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