BayesianFROC (version 0.3.0)

stanfitExtended: stanfitExtended, an S4 class inherited from the S4 class stanfit

Description

Inherits from the class stanfit which is an S4 class defined in the package rstan :

Slots

plotdataMRMC

Plot data for MRMC case.

plotdata

This is a data frame with four components which is used to draw curves such as FROC curves and AFROC curves. So, this slot includes the component:

fit@plotdata$x.AFROC,

fit@plotdata$y.AFROC,

fit@plotdata$x.FROC,

fit@plotdata$y.AFROC

where fit is an object of class stanfitExtended.

For example, we can use this slot such as plot(fit@plotdata$x.AFROC, fit@plotdata$y.AFROC ) The author think this slot is not good because it increases the object size.

dataList

An FROC dataset. Using the dataset, the fitting has done.

studyDesign

A character, e.g., "srsc.per.image", "srsc.per.lesion", according to False Positive Fraction (FPF) is per image or per lesion.

metadata

An additional data calculated from dataList, such as cumulative hits and false alarms,...,etc.

WAIC

A WAIC calculated by the function waic .

convergence

A logical R object TRUE or FALSE. If TRUE, then it means your model is good in the R hat criterion.

PreciseLogLikelihood

This is TRUE or FALSE. If TRUE, then target formulation is used in the stan file. However, non-target formulation has warning for non-linear Jacobian issue. So, the author use target formulations for all .stan files, and thus this slot is now, redandunt.

chisquare

This is a chi square calculated with Expected A Posterior estimates, i.e., the posterior mean estimates. Chi square statistic is \(\chi^2 (Data|\theta)\), there are three simple ways to get it.

(1) \( \int \chi^2(Data|\theta ) \pi(\theta|Data)d\theta \)

(2) \( \chi^2(Data|\int \theta \pi(\theta|Data)d\theta) \)

(3) \( \int \chi^2(Data|\theta ) f(Data|\theta)\pi(\theta|Data)d\theta \)

where, \(f( Data|\theta )\) denotes a likelihood and \(\pi(\theta| Data )\) is a posterior. This slot retains the (2)

See also ppp()

index

This is for programming phase.

Divergences

This is the number of the divergence transitions in the MCMC simulation.

MCMC.Iterations

A MCMC iterations which does not count the burn-in period.

Divergence.rate

A divergence rate, that is the number of the divergence iterations over total MCMC iterations. Burn-in period is not included.

model_name

A slot of the stanfit which is an S4 class defined in the rstan package.

model_pars

A slot of the stanfit which is an S4 class in the package rstan.

par_dims

A slot of the stanfit which is an S4 class in the package rstan.

mode

A slot of the stanfit which is an S4 class in the package rstan.

sim

A slot of the stanfit which is an S4 class in the package rstan.

inits

A slot of the stanfit which is an S4 class in the package rstan.

stan_args

A slot of the stanfit which is an S4 class in the package rstan.

stanmodel

A slot of the stanfit which is an S4 class in the package rstan.

date

A slot of the stanfit which is an S4 class in the package rstan.

.MISC

A slot of the stanfit which is an S4 class in the package rstan.

Details

Revised in 2019.Jun 5 Revised in 2019 Oct 19 Revised in 2019 Nov 25

-------- To read the table of R object of class stanfit in case of MRMC ----------------------------

* The AUC denoted by AA[modalityID , readerID] are shown.

For example, AA[2,3] means the AUC of the 2 nd modality and the 3 rd reader.

* The column of 2.5% and 97.5% means the lower and upper bounds of the 95