range2sigma(x, stat="ES", n=5, nGroups=1, CIlevel=0.95, collapse=TRUE, dstTarget=100, conversion="m2cm")
"ES"
(extreme spread), "FoM"
(figure of merit), or "D"
(bounding box diagonal) indicating which range statistic is given in x
. Elements correspond to those in x
in the sense that the second element of stat
indicates the statistic for the second element of x
. If all elements of x
are the same kind of statistic, stat
only needs to indicate it once.x
is the average of individually-measured range statistics from several groups.0.5
, 0.9
, 0.95
, 0.99
, the CI is based on the corresponding quantiles of the Monte Carlo distribution of the range statistic for given n
and nGroups
. If not, CI can only be calculated for extreme spread using a Patnaik chi^2 approximation to the conditional distribution as suggested by Taylor and Grubbs (1975).getMOA
.getMOA
.DFdistr
with results form a Monte Carlo simulation. If the value of n
is not among those simulated (but is less than 100), a spline interpolation between the neighboring simulated values of the statistic's coefficient of variation is used.If the Rayleigh sigma should be calculated for a value of n
that was not simulated (but is less than 100), a spline interpolation between the neighboring simulated values is used.
Details for the calculation can be found under
http://ballistipedia.com/index.php?title=Range_Statistics
If package shiny
is installed, an interactive web app for this functionality can be run with runGUI("range")
.
DFdistr
,
efficiency
,
getRayParam
,
getMaxPairDist
,
getBoundingBox
es <- getMaxPairDist(DFscar17)$d
fom <- getBoundingBox(DFscar17)$FoM
d <- getBoundingBox(DFscar17)$diag
range2sigma(c(es, fom, d), stat=c("ES", "FoM", "D"),
n=nrow(DFscar17), nGroups=1, CIlevel=0.9)
# compare with Rayleigh sigma estimate from using
# (x,y)-coordinates of all shots
getRayParam(DFscar17, level=0.9)
Run the code above in your browser using DataLab