# R/prior_print.R In BayesianFROC: FROC Analysis by Bayesian Approaches

#### Documented in prior_print_MRMCprior_print_srsc

```#' @title Print What Prior Are Used
#' @description Prints prior in R console
#' @param prior  An integer, representing type of Prior
#'
#' @return none
#' @export
#'
#' @examples
#'
#'    prior_print_srsc()
#'
prior_print_srsc  <- function(prior=0) {

message("\n---------------------- Prior --------")

if (prior==-1) {

message("\n*  prior:
w,m  ~  Gaussian(0,111);
v,dz ~  uniform(0,111);

where uniform(a,b) denotes the uniform distribution on {t; a<t<b }
and Gaussian(a,b) denotes the Gaussian of mean:a and variance: b. ...SD?????

* Non-Informative
* proper

")#message

}

if (prior==0) {

message("\n* we use the following prior:

w ~ uniform(-inf,inf);
dz ~ uniform(   0,inf);
m ~ uniform(-inf,inf);
v ~ uniform(   0,inf);

where uniform(a,b) denotes the uniform distribution
whose support is the interval {t; a<t<b }.

So, this prior is the non-informative improper prior.

* Non-Informative
* Improper

")#message

}

if(prior == 1){
message("\n* we use the following prior:

w ~  uniform(-111,111);
for(cd in 1:C-1) dz[cd] ~  uniform(   0,111);
m ~  uniform(-111,111);
v ~  uniform(   0,111);

So, this prior is the non-informative proper prior.

* Non-Informative
* proper

")#message
}

if(prior == 2){
message("\n* test prior

")#message
}

message("\n------------------------------------------")

}#function

#' @title Print What Prior Are Used
#' @description Prints prior in R console
#' @param prior  An integer, representing type of Prior
#'
#' @return none
#' @export
#'
#' @examples
#'
#'    prior_print_MRMC()
#'
prior_print_MRMC  <- function(prior=0) {

message("\n---------------------- Prior --------")

if (prior==-1) {

message("\n*   prior:

w, mu ~  uniform(-111,111);

dz,v ~  uniform(0,111);

where uniform(a,b) denotes the uniform distribution on {t; a<t<b }

* Non-Informative
* proper

")#message
}

if (prior==1) {

message("\n*   prior:

w ~ Gaussian(0,111);
mu  ~ Gaussian(0,111);

v  ~ uniform(0,111);
dz ~  uniform(0,111);
hyper_v ~ uniform(0,111);

where uniform(a,b) denotes the uniform distribution on {t; a<t<b }
and Gaussian(a,b) denotes the Gaussian of mean:a and variance: b. ...SD?????

* Non-Informative
* proper

")#message

}

if (prior==0) {

message("\n* we use the following prior:

w ~ uniform(-inf,inf);
for(cd in 1:C-1) dz[cd] ~ uniform(   0,inf);
m ~ uniform(-inf,inf);
v ~ uniform(   0,inf);

where uniform(a,b) denotes the uniform distribution
whose support is the interval {t; a<t<b }.

So, this prior is the non-informative improper prior.

* Non-Informative
* Improper

")#message

}

if(prior == 1){
message("\n* we use the following prior:

w ~  uniform(-111,111);
for(cd in 1:C-1) dz[cd] ~  uniform(   0,111);
m ~  uniform(-111,111);
v ~  uniform(   0,111);

So, this prior is the non-informative proper prior.

* Non-Informative
* proper

")#message
}

message("\n------------------------------------------")

}#function
```

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BayesianFROC documentation built on Jan. 13, 2021, 5:22 a.m.