The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

PriorGen old/new features ver 1

Basic findbeta updated

library(PriorGen)

## Loading required package: rootSolve

## Loading required package: nleqslv

findbeta(themedian = 0.5,lower.v = T,percentile = 0.999,percentile.value = 0.999)

## $parameters
## a b 
## 1 1 
## 
## $summary
##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## 0.0005798 0.2548675 0.5011664 0.5009285 0.7471612 0.9999125 
## 
## $input
##        themedian       percentile percentile.value 
##            0.500            0.999            0.999 
## 
## attr(,"class")
## [1] "PriorGen"

#findbeta(themode = 0.5,lower.v = T,percentile = 0.80,percentile.value = 0.95)
fb_per=findbeta(themean = 0.5,lower.v = T,percentile = 0.90,percentile.value = 0.95)
fb_per$parameters

##         a         b 
## 0.6658199 0.6658199

fb_per$summary

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## 0.0000004 0.1923723 0.4975507 0.4977591 0.8030204 0.9999862

fb_per$input

##          themean       percentile percentile.value 
##             0.50             0.90             0.95

print_PriorGen(fb_per)

## [1] "The desired Beta distribution that satisfies the specified conditions is: Beta(0.67,0.67). Verification: The percentile value 0.95 corresponds to the 90th percentile"

Raw findbeta (mean/median/mode/variance/range input)

library(PriorGen)
findbeta_raw(themedian = 0.5,therange = c(0,1))

## $parameters
## a b 
## 1 1 
## 
## $summary
##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## 0.0000875 0.2528388 0.4988336 0.4990715 0.7451325 0.9994202 
## 
## $input
##                themedian scalemetric_var_or_range 
##                      0.5                      1.0 
## 
## attr(,"class")
## [1] "PriorGen"

#findbeta_raw(themode = 0.5,therange = c(0,1))
fb_raw=findbeta_raw(themean = 0.8,thevariance = 0.2)
fb_raw$parameters

##        a        b 
## 5.157879 1.289470

fb_raw$summary

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.1156  0.7171  0.8315  0.8004  0.9130  0.9997

fb_raw$input

##                  themean scalemetric_var_or_range 
##                0.8000000                0.0408861

Abstract findbeta (General statements input)

library(PriorGen)
findbeta_abstract(themean.cat = "Low",thevariance.cat = "High")

## $parameters
##        a        b 
## 2.136044 4.984102 
## 
## $summary
##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
## 0.004837 0.178582 0.281257 0.301772 0.404865 0.869466 
## 
## $input
##          themean      scalemetric percentile.value 
##           0.3000           0.1075           0.9990 
## 
## attr(,"class")
## [1] "PriorGen"

#findbeta_abstract(themean.cat = "Very low",thevariance.cat = "Low") 
fb_abstract=findbeta_abstract(themean.cat =  "Low",thevariance.cat = "High")
fb_abstract$parameters

##        a        b 
## 2.136044 4.984102

fb_abstract$summary

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
## 0.004837 0.178582 0.281257 0.301772 0.404865 0.869466

fb_abstract$input

##          themean      scalemetric percentile.value 
##           0.3000           0.1075           0.9990

Panel findbeta (Vector input)

library(PriorGen)
#findbeta_panel(themedian.vec = c(0.2,0.02,0.5,0.03,0.04,0.05)) 
findbeta_panel(themode.vec = c(0.2,0.02,0.5,0.03,0.04,0.05))

## $parameters
##         a         b 
##  4.570939 22.935768 
## 
## $summary
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.01882 0.11591 0.15828 0.16678 0.20848 0.51874 
## 
## $input
##          themode       percentile       scalevalue percentile.value 
##           0.1400           0.9999           0.4800           0.4990 
## 
## attr(,"class")
## [1] "PriorGen"

fb_panel=findbeta_panel(themean.vec = c(0.2,0.02,0.5,0.03,0.04,0.05)) 
fb_panel$parameters

##        a        b 
## 11.90200 73.11232

fb_panel$summary

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.04516 0.11378 0.13739 0.14026 0.16347 0.30894

fb_panel$input

##          themean       percentile       scalevalue percentile.value 
##        0.1400000        0.9999000        0.0355600        0.2773494

Basic findbetaqq updated (Percentiles input)

library(PriorGen)
fb_qq=findbetaqq(percentile.value1 = 0.3,percentile1 = 0.20,
                 percentile.value2 = 0.7,percentile2 = 0.97) 
fb_qq$parameters

##        a        b 
## 4.754100 6.398365

fb_qq$summary

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.06502 0.32446 0.42170 0.42666 0.52329 0.89435

fb_qq$input

## percentile.value1       percentile1 percentile.value2       percentile2 
##              0.30              0.20              0.70              0.97

Basic findbetamupsi updated (Hierarchical input + choice of root function)

library(PriorGen)
fb_mupsi_RS=findbetamupsi(themean=0.20, percentile=0.99, lower.v=TRUE,
              percentile.value=0.30, psi.percentile=0.90,
              percentile.median=0.60, percentile95value=0.80,root.method="multiroot")
fb_mupsi_RS$parameters

## NULL

fb_mupsi_RS$summary

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
## 0.000000 0.008379 0.085610 0.203784 0.320677 0.999995

fb_mupsi_RS$input

##           themean        percentile  percentile.value    psi.percentile 
##              0.20              0.99              0.30              0.90 
## percentile.median percentile95value 
##              0.60              0.80

fb_mupsi_NL=findbetamupsi(themean=0.20, percentile=0.99, lower.v=TRUE,
              percentile.value=0.30, psi.percentile=0.90,
              percentile.median=0.60, percentile95value=0.80,root.method="nleqslv")
fb_mupsi_RS$parameters

## NULL

fb_mupsi_NL$parameters

## NULL

# Results are similar

Raw findbetamupsi updated (Hierarchical input)

library(PriorGen)
fb_mupsi_raw=findbetamupsi_raw(themean=0.20,thevariance = 0.05, thepsi=0.15)
fb_mupsi_raw$parameters

## NULL

fb_mupsi_raw$summary

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## 0.0000000 0.0000000 0.0000103 0.1935947 0.1337335 1.0000000

fb_mupsi_raw$input

##          themean     thevariances       percentile percentile.value 
##        0.2000000        0.0500000        0.9999000        0.3645263 
##           thepsi 
##        0.1500000

Abstract findbetamupsi updated (Hierarchical input)

library(PriorGen)
fb_mupsi_abstract=findbetamupsi_abstract(themean="Average",thevariance = "Very high", 
                                         psi.percentile=0.90,percentile.median=0.999,
                                         percentile95value=0.9999)
fb_mupsi_abstract$parameters

## NULL

fb_mupsi_abstract$summary

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.00000 0.05677 0.64303 0.54865 0.99077 1.00000

fb_mupsi_abstract$input

##           themean        percentile  percentile.value    psi.percentile 
##         0.5500000         0.9999000         0.9974181         0.9000000 
## percentile.median percentile95value 
##         0.9990000         0.9999000

Panel findbetamupsi updated (Hierarchical input)

library(PriorGen)
fb_mupsi_panel=findbetamupsi_panel(themean=c(0.1,0.5,0.6,0.3,0.05,0.01,0.3), 
                                   psi.percentile=0.90, percentile.median=0.50,
                                   percentile95value=0.60)
fb_mupsi_panel$parameters

## NULL

fb_mupsi_panel$summary

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## 0.0000001 0.1293974 0.2387243 0.2681315 0.3763673 0.9607058

fb_mupsi_panel$input

##           themean        percentile  percentile.value    psi.percentile 
##         0.2657143         0.9999000         0.4656722         0.9000000 
## percentile.median percentile95value 
##         0.5000000         0.6000000

Plot for findbeta

library(PriorGen)
fb_pr=findbeta(themean = 0.5,lower.v = T,percentile = 0.999,percentile.value = 0.999) 
plot(fb_pr,main="Elicited beta prior \n(Percentile)",ylab = "Density",lwd=3,type="l",xlab="")

# Plot for finbeta_raw

library(PriorGen)
fb_raw=findbeta_raw(themean = 0.5,thevariance = 0.5) 
plot(fb_raw,main="Elicited beta prior \n(Raw)",ylab = "Density",lwd=3,type="l",xlab="")

# Plot for findbeta_abstract

library(PriorGen)
fb_abstract=findbeta_abstract(themean.cat = "Low",thevariance.cat = "High") 
plot(fb_abstract,main="Elicited beta prior \n(Abstract)",ylab = "Density",lwd=3,type="l",xlab="")

Plot for findbeta_panel

library(PriorGen)
fb_panel1=findbeta_panel(themean.vec = c(0.2,0.02,0.5,0.03,0.04,0.05)) 
fb_panel2=findbeta_panel(themean.vec = c(0.2,0.02,0.5,0.4,0.04,0.05)) 
plot(fb_panel1,main="Elicited beta prior  \n(Panel)",ylab = "Density",lwd=3,type="l",xlab="")
lines(fb_panel2,lwd=3,type="l",lty=2)
legend("topright",c("Panel 1", "Panel 2"),lty = c(1,2),lwd=3)

Plot for findbetaqq

library(PriorGen)

fb_qq=findbetaqq(percentile.value1 = 0.3,percentile1 = 0.20,
percentile.value2 = 0.7,percentile2 = 0.97) 

plot(fb_qq,main="Elicited beta prior \n(Percentiles method)",ylab = "Density",lwd=3,type="l",xlab="")

Plots for finbetamupsi

library(PriorGen)
fb_mupsi=findbetamupsi(themean=0.20, percentile=0.99, lower.v=TRUE,
              percentile.value=0.30, psi.percentile=0.90,
              percentile.median=0.50, percentile95value=0.60)
#par(mfrow=c(1,3))
#plot(density(fb_mupsi$param_upper$at),lwd=3,main="Density plot for samples of a=mu*psi") # 
#plot(density(fb_mupsi$param_upper$bt),lwd=3,main="Density plot for samples of b=mu*(1-psi)") # 
plot(fb_mupsi,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",xlab="")
fb_mupsi1=findbetamupsi(themean=0.30, percentile=0.8, lower.v=TRUE,
              percentile.value=0.30, psi.percentile=0.90,
              percentile.median=0.70, percentile95value=0.80)
lines(fb_mupsi1,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",lty=2,col="gray")
legend("topright",c("Basic","Basic1"),col=c("black","gray"),lty=1:2,lwd=3)

Plots for findbetamupsi_raw

library(PriorGen)
fb_mupsi_raw=findbetamupsi_raw(themean=0.20, thevariance = 0.1, thepsi=0.15)
#par(mfrow=c(1,3))
#plot(density(fb_mupsi_abstract$param_upper$at),lwd=3,main="Density plot for samples of a=mu*psi") # 
#plot(density(fb_mupsi_abstract$param_upper$bt),lwd=3,main="Density plot for samples of b=mu*(1-psi)") # 
plot(fb_mupsi_raw,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",xlab="")
fb_mupsi_raw1=findbetamupsi_raw(themean=0.30, thevariance = 0.15, thepsi=0.15)
lines(fb_mupsi_raw1,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",lty=2,col="gray")
legend("topright",c("Raw","Raw1"),col=c("black","gray"),lty=1:2,lwd=3)

Plots for findbetamupsi_abstract

library(PriorGen)
fb_mupsi_abstract=findbetamupsi_abstract(themean="Low", thevariance = "High", 
psi.percentile=0.90, percentile.median=0.95, percentile95value=0.98)
#par(mfrow=c(1,3))
#plot(density(fb_mupsi_abstract$param_upper$at),lwd=3,main="Density plot for samples of a=mu*psi") # 
#plot(density(fb_mupsi_abstract$param_upper$bt),lwd=3,main="Density plot for samples of b=mu*(1-psi)") # 
plot(fb_mupsi_abstract,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",xlab="")
fb_mupsi_abstract1=findbetamupsi_abstract(themean="Very low", thevariance = "Average",
                                          psi.percentile=0.90,percentile.median=0.95, 
                                          percentile95value=0.98)
lines(fb_mupsi_abstract1,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",lty=2,col="gray")
legend("topright",c("Abstract","Abstract1"),col=c("black","gray"),lty=1:2,lwd=3)

Plots for findbetamupsi_panel

library(PriorGen)
fb_mupsi_panel=findbetamupsi_panel(themean=c(0.1,0.5,0.05,0.01,0.4,0.2), psi.percentile=0.90,
                                   percentile.median=0.50, percentile95value=0.60)
#par(mfrow=c(1,3))
#plot(density(fb_mupsi_panel$param_upper$at),lwd=3,main="Density plot for samples of a=mu*psi") # 
#plot(density(fb_mupsi_panel$param_upper$bt),lwd=3,main="Density plot for samples of b=mu*(1-psi)") # 
plot(fb_mupsi_panel,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",xlab="")
fb_mupsi_panel1=findbetamupsi_panel(themean=c(0.1,0.5,0.05,0.01,0.6,0.65), psi.percentile=0.90,
              percentile.median=0.80, percentile95value=0.90)
lines(fb_mupsi_panel1,main="Elicited beta prior \n(Hierarchical top level)",
              ylab = "Density",lwd=3,type="l",lty=2,col="gray")
legend("topright",c("Panel","Panel1"),col=c("black","gray"),lty=1:2,lwd=3)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.