Build a probability distribution (one option for creating a prior distribution) by clicking or dragging a plot.
TkBuildDist(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)TkBuildDist2( min=0, max=1, nbin=10, logspline=TRUE)
Both functions return a list with the breaks that were used the
logspline fit (if logspline is TRUE), the x-values clicked on
(for TkBuildDist), and the proportion of the distribution
within each interval (for TkBuildDist2 or if intervals
is TRUE).
A starting set of data points, will default to a sequence of uniform values.
The minimum value for the histogram
The maximum value for the histogram
The number of bins for the histogram
Logical, whether to include a logspline curve on the plot and in the output.
Logical, should the logspline fit be based on the interval counts rather than the clicked data points, also should the interval summary be returned.
Greg Snow 538280@gmail.com
Bothe of these functions will open a Tk window to interact with. The window will show a histogram (the defaults will show a uniform distribution), optionally a logspline fit line will be included as well. Including the logspline will slow things down a bit, so you may want to skip it on slow computers.
If you use the TkBuildDist function then a left click on the
histogram will add an additional point to the histogram bar clicked on
(the actual x-value where clicked will be saved, returned, and used in
the optional logspline unless intervals is TRUE). Right
clicking on the histogram will remove the point closest to where
clicked (based only on x), which will usually have the effect of
decreasing the clicked bar by 1, but could affect the neigboring bar
if you click near the edge or click on a bar that is 0.
If you use the TkBuildDist2 function then the individual bars
can be adjusted by clicking at the top of a bar and dragging up or
down, or clicking at what you want the new height of the bar to be.
As the current bar is adjusted the other bars will adjust in the
oposite direction proportional to their current heights.
The logspline fit assumes the basis for the distribution is the real
line, the min and max arguments only control the
histogram and where values can be changed.
The logspline package
if(interactive()){
tmp1 <- TkBuildDist()
tmp2 <- TkBuildDist2()
}
Run the code above in your browser using DataLab