prev-class | R Documentation |
"prev"
The "prev"
class represents output from Bayesian true prevalence
estimation models.
Objects of class "prev"
are created by truePrev
, truePrevMulti
, truePrevMulti2
and truePrevPools
.
Objects of class "prev"
contain the following four slots:
par
:A list of input parameters
model
:The fitted Bayesian model, in BUGS language (S3 class "prevModel"
)
mcmc
:A list, with one element per chain, of the simulated true prevalences, sensitivities and specificities
diagnostics
:A list with elements for the Deviance Information Criterion ($DIC
), the Brooks-Gelman-Rubin statistic ($BGR
), and in the case of truePrevMulti
and truePrevMulti2
, the Bayes-P statistic
($bayesP
)
Brecht Devleesschauwer <brechtdv@gmail.com>
truePrev
, truePrevMulti
, truePrevMulti2
, truePrevPools
show-methods
, print-methods
, summary-methods
, convert-methods
, plot-methods
, plot-methods-coda
## Taenia solium cysticercosis in Nepal SE <- list(dist = "uniform", min = 0.60, max = 1.00) SP <- list(dist = "uniform", min = 0.75, max = 1.00) TP <- truePrev(x = 142, n = 742, SE = SE, SP = SP) ## Summarize estimates per chain summary(TP) ## Diagnostic plots par(mfrow = c(2, 2)) plot(TP) ## Generic plots from package coda par(mfrow = c(1, 1)) densplot(TP) traceplot(TP) gelman.plot(TP) autocorr.plot(TP) ## Use 'slotNames()' to see the slots of object TP slotNames(TP) ## Every slot can be accessed using the '@' operator ## Use 'str()' to see the structure of each object str(TP@par) # input parameters str(TP@model) # fitted model str(TP@mcmc) # simulated TP, SE, SP str(TP@diagnostics) # DIC and BGR (and bayesP) ## Each element of TP@mcmc inherits from coda class 'mcmc.list' ## List all available methods for this class methods(class = "mcmc.list") ## List all available functions in the coda package library(help = "coda") ## Highest Posterior Density interval, from coda package coda::HPDinterval(TP@mcmc$TP)
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