在主观概率评估中，需要引出受试者相信的分布。它可以通过让受试者操纵直方图的每个频率区间的相对高度来实现。即概率分布，包络线得到保持累积和（P_i）=1的形状。这怎么能用 R 来完成？是否已经有我可以构建的包？
或者：如何在电子表格应用程序（excel、oo calc、google 电子表格）中完成？
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这是我使用 tkrplot 包和可选的 logspline 包放在一起的一些代码。
只需运行该函数（您可以更改参数，但要进行测试，您可以使用默认值进行测试）然后在出现的新窗口中单击绘图，左键单击将添加一个单击点，右（或中间）点击将删除最接近您点击的点。
我可能会稍微清理一下，并将其包含在 TeachingDemos 包的未来版本中（因此非常欢迎评论/建议）。
TkBuildDist <- function( x=seq(min+(max-min)/nbin/2,
max-(max-min)/nbin/2,
length.out=nbin),
min=0, max=10, nbin=10, logspline=TRUE,
intervals=FALSE) {
if(logspline) logspline <- require(logspline)
require(tkrplot)
xxx <- x
brks <- seq(min, max, length.out=nbin+1)
nx <- seq( min(brks), max(brks), length.out=250 )
lx <- ux <- 0
first <- TRUE
replot <- if(logspline) {
if(intervals) {
function() {
hist(xxx, breaks=brks, probability=TRUE,xlab='', main='')
xx <- cut(xxx, brks, labels=FALSE)
fit <- oldlogspline( interval = cbind(brks[xx], brks[xx+1]) )
lines( nx, doldlogspline(nx,fit), lwd=3 )
if(first) {
first <<- FALSE
lx <<- grconvertX(min, to='ndc')
ux <<- grconvertX(max, to='ndc')
}
}
} else {
function() {
hist(xxx, breaks=brks, probability=TRUE,xlab='', main='')
fit <- logspline( xxx )
lines( nx, dlogspline(nx,fit), lwd=3 )
if(first) {
first <<- FALSE
lx <<- grconvertX(min, to='ndc')
ux <<- grconvertX(max, to='ndc')
}
}
}
} else {
function() {
hist(xxx, breaks=brks, probability=TRUE,xlab='',main='')
if(first) {
first <<- FALSE
lx <<- grconvertX(min, to='ndc')
ux <<- grconvertX(max, to='ndc')
}
}
}
tt <- tktoplevel()
tkwm.title(tt, "Distribution Builder")
img <- tkrplot(tt, replot, vscale=1.5, hscale=1.5)
tkpack(img, side='top')
tkpack( tkbutton(tt, text='Quit', command=function() tkdestroy(tt)),
side='right')
iw <- as.numeric(tcl('image','width',tkcget(img,'-image')))
mouse1.down <- function(x,y) {
tx <- (as.numeric(x)-1)/iw
ux <- (tx-lx)/(ux-lx)*(max-min)+min
xxx <<- c(xxx,ux)
tkrreplot(img)
}
mouse2.down <- function(x,y) {
if(length(xxx)) {
tx <- (as.numeric(x)-1)/iw
ux <- (tx-lx)/(ux-lx)*(max-min)+min
w <- which.min( abs(xxx-ux) )
xxx <<- xxx[-w]
tkrreplot(img)
}
}
tkbind(img, '<ButtonPress-1>', mouse1.down)
tkbind(img, '<ButtonPress-2>', mouse2.down)
tkbind(img, '<ButtonPress-3>', mouse2.down)
tkwait.window(tt)
out <- list(x=xxx)
if(logspline) {
if( intervals ) {
xx <- cut(xxx, brks, labels=FALSE)
out$logspline <- oldlogspline( interval = cbind(brks[xx], brks[xx+1]) )
} else {
out$logspline <- logspline(xxx)
}
}
if(intervals) {
out$intervals <- table(cut(xxx, brks))
}
out$breaks <- brks
return(out)
}
这是另一个允许拖动条形高度的版本：
TkBuildDist2 <- function( min=0, max=1, nbin=10, logspline=TRUE) {
if(logspline) logspline <- require(logspline)
require(tkrplot)
xxx <- rep( 1/nbin, nbin )
brks <- seq(min, max, length.out=nbin+1)
nx <- seq( min, max, length.out=250 )
lx <- ux <- ly <- uy <- 0
first <- TRUE
replot <- if(logspline) {
function() {
barplot(xxx, width=diff(brks), xlim=c(min,max), space=0,
ylim=c(0,0.5), col=NA)
axis(1,at=brks)
xx <- rep( 1:nbin, round(xxx*100) )
capture.output(fit <- oldlogspline( interval = cbind(brks[xx], brks[xx+1]) ))
lines( nx, doldlogspline(nx,fit)*(max-min)/nbin, lwd=3 )
if(first) {
first <<- FALSE
lx <<- grconvertX(min, to='ndc')
ly <<- grconvertY(0, to='ndc')
ux <<- grconvertX(max, to='ndc')
uy <<- grconvertY(0.5, to='ndc')
}
}
} else {
function() {
barplot(xxx, width=diff(brks), xlim=range(brks), space=0,
ylim=c(0,0.5), col=NA)
axis(at=brks)
if(first) {
first <<- FALSE
lx <<- grconvertX(min, to='ndc')
ly <<- grconvertY(0, to='ndc')
ux <<- grconvertX(max, to='ndc')
uy <<- grconvertY(0.5, to='ndc')
}
}
}
tt <- tktoplevel()
tkwm.title(tt, "Distribution Builder")
img <- tkrplot(tt, replot, vscale=1.5, hscale=1.5)
tkpack(img, side='top')
tkpack( tkbutton(tt, text='Quit', command=function() tkdestroy(tt)),
side='right')
iw <- as.numeric(tcl('image','width',tkcget(img,'-image')))
ih <- as.numeric(tcl('image','height',tkcget(img,'-image')))
md <- FALSE
mouse.move <- function(x,y) {
if(md) {
tx <- (as.numeric(x)-1)/iw
ty <- 1-(as.numeric(y)-1)/ih
w <- findInterval(tx, seq(lx,ux, length=nbin+1))
if( w > 0 && w <= nbin && ty >= ly && ty <= uy ) {
xxx[w] <<- 0.5*(ty-ly)/(uy-ly)
xxx[-w] <<- (1-xxx[w])*xxx[-w]/sum(xxx[-w])
tkrreplot(img)
}
}
}
mouse.down <- function(x,y) {
md <<- TRUE
mouse.move(x,y)
}
mouse.up <- function(x,y) {
md <<- FALSE
}
tkbind(img, '<Motion>', mouse.move)
tkbind(img, '<ButtonPress-1>', mouse.down)
tkbind(img, '<ButtonRelease-1>', mouse.up)
tkwait.window(tt)
out <- list(breaks=brks, probs=xxx)
if(logspline) {
xx <- rep( 1:nbin, round(xxx*100) )
out$logspline <- oldlogspline( interval = cbind(brks[xx], brks[xx+1]) )
}
return(out)
}
于 2011-01-26T21:31:40.790 回答