Nothing
library(BayesianFROC)
#1) Build the data for singler reader and single modality case.
# To apply functions in the rstan package, we have to chage the class.
# fit_Bayesisan_FROC() return the object of some inherited S4 class from the S4 class stanfit.
# Thus to apply the generic function or any functions for stanfit, we have to change the class
# by the code
#
# fit.stanfit <- as(fit, "stanfit")
#
# where fit is a return value of the fit_Bayesisan_FROC().
data.example <- 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
data.example <- give_name_srsc_data(data.example)
viewdata(data.example)
draw.CFP.CTP.from.dataList(data.example)
fit <- fit_Bayesian_FROC(data.example,cha = 3)
fit.stanfit <- as(fit, "stanfit") # Please Change the S4 class from the inherited S4 class to the stanfit S4 class to apply the rstan functions.
summary(fit.stanfit)
print(fit.stanfit)
rstan::traceplot(fit.stanfit,par=c("A"))
rstan::stan_dens(fit.stanfit,par=c("A"))
check_divergences(fit.stanfit)
check_hmc_diagnostics(fit.stanfit)
pairs(fit.stanfit,pars=c("A","lp__","m"))
get_posterior_mean(fit.stanfit)
check_rhat(fit.stanfit)
rstan::stan_hist(fit.stanfit)
rstan::stan_rhat(fit.stanfit)
# plot() cause the error: Error in as.double(y) : cannot coerce type 'S4' to vector of type 'double'
# plot(fit.stanfit)
# plot(fit.stanfit,pars=c("l","p"))
# plot(fit.stanfit,pars=c("v","m"))
# plot(fit.stanfit,pars=c("w", "z" ,"dz"))
message("
# The R scripts used in the demo.
# example data
", crayon::bgBlack$cyan$bold$italic$underline("data.example <- list( "),"
", crayon::bgBlack$cyan$bold$italic$underline(" c=c(3,2,1), #Confidence level"),"
", crayon::bgBlack$cyan$bold$italic$underline("h=c(97,32,31), #Number of hits for each confidence level"),"
", crayon::bgBlack$cyan$bold$italic$underline("f=c(1,14,74), #Number of false alarms for each confidence level"),"
", crayon::bgBlack$cyan$bold$italic$underline(" NL=259, #Number of lesions"),"
", crayon::bgBlack$cyan$bold$italic$underline(" NI=57, #Number of images"),"
", crayon::bgBlack$cyan$bold$italic$underline(" C=3) #Number of confidence level"),"
# Give a name
", crayon::bgBlack$cyan$bold$italic$underline("data.example <- give_name_srsc_data(data.example)"),"
# View data by table
", crayon::bgBlack$cyan$bold$italic$underline("viewdata(data.example)"),"
# Draw empirical FROC curve
", crayon::bgBlack$cyan$bold$italic$underline("draw.CFP.CTP.from.dataList(data.example)"),"
# Fit a model to data
", crayon::bgBlack$cyan$bold$italic$underline("fit <- fit_Bayesian_FROC(data.example,cha = 3)"),"
# change S4 class from stanfitExtended to stanfit
", crayon::bgBlack$cyan$bold$italic$underline("fit.stanfit <- as(fit, \"stanfit\")")," # Please Change the S4 class from the inherited S4 class to the stanfit S4 class to apply the rstan functions.
# In the following, we use functions from the package rstan
", crayon::bgBlack$cyan$bold$italic$underline("summary(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("print(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("rstan::traceplot(fit.stanfit,par=c(\"A\"))"),"
", crayon::bgBlack$cyan$bold$italic$underline("rstan::stan_dens(fit.stanfit,par=c(\"A\"))"),"
", crayon::bgBlack$cyan$bold$italic$underline("check_divergences(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("check_hmc_diagnostics(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("pairs(fit.stanfit,pars=c(\"A\",\"lp__\",\"m\"))"),"
", crayon::bgBlack$cyan$bold$italic$underline("get_posterior_mean(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("check_rhat(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("rstan::stan_hist(fit.stanfit)"),"
", crayon::bgBlack$cyan$bold$italic$underline("rstan::stan_rhat(fit.stanfit)"),"
")
# Demo finished !!
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.