Description Usage Arguments Details Value References See Also Examples
View source: R/ConfirmConvergence.R
Calculates the maximum and the minimal values of R hat over all parameters.
In addition, it returns a loginal R object whether R hat is good (TRUE
) or bad (FALSE
).
1 | ConfirmConvergence(StanS4class, summary = TRUE, digits = 2)
|
StanS4class |
An S4 object of the class |
summary |
Logical: |
digits |
A positive integer, indicating digits for R hat statistics. |
Evaluates convergence criterion based on only the R hat statistics for a fitted model object. Revised Nov 23.
Logical: TRUE
of FALSE
. If model converges ( all R hat are closed to 1) then it is TRUE
, and if not( some R hat is far from 1), then FALSE
.
Gelman A. & Rubin, D.B. (1992). Inference from Iterative Simulation Using Multiple Sequences, Statistical Science, Volume 7, Number 4, 457-472.
check_rhat()
, which is made by Betanalpha.
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#================The first example======================================
#((Primitive way)).
#1) Build the data for a singler reader and a single modality case.
dat <- list(c=c(3,2,1), #Confidence level
h=c(97,32,31), #Number of hits for each confidence level
f=c(1,14,74), #Number of false alarms for each confidence level
NL=259, #Number of lesions
NI=57, #Number of images
C=3) #Number of confidence level
# where, c denotes Confidence level,
# h denotes number of Hits for each confidence level,
# f denotes number of False alarms for each confidence level,
# NL denotes Number of Lesions,
# NI denotes Number of Images,
#2) Fit the FROC model.
#Since the above dataset "dat" are single reader and single modality,
#the following function fit the non hierarchical model.
fit <- BayesianFROC::fit_Bayesian_FROC(dat,ite=1111)
# Where, the variable "ite" specifies the iteration of MCMC samplings.
# Larger iteration is better.
#3.1) Confirm whether our estimates converge.
ConfirmConvergence(fit)
# By the above R script,
# the diagnosis of convergence will be printed in the R (R-studio) console.
# The diagnosis is based on only the R hat statistic.
# It also return the logical vector indicating whether or not the MCMC converge,
# if MCMC converges, then the return value is TRUE and if not, then FALSE.
# This logical return value is used in this package development
# and the user should not be interested.
# The following was useful for programming.
#3.2) The return value is TRUE or FALSE.
x <- ConfirmConvergence(fit)
#3.3) If you do not want to print the results in the R (Studio) console, then
x <- ConfirmConvergence(fit,summary=FALSE)
# 2019.05.21 Revised.
# 2019.12.02 Revised.
## End(Not run)# dontrun
|
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