View source: R/getRangeStatCI.R
getRangeStatCI | R Documentation |
Returns the confindence interval for given range statistics: extreme spread, figure of merit, bounding box diagonal. Calculations assume a circular bivariate normal shot distribution with 0 mean.
getRangeStatCI(x, stat="ES", n, nGroups, CIlevel=0.95,
collapse=TRUE, dstTarget, conversion5)
x |
a numerical vector with values for extreme spread (ES), figure of merit (FoM), or the diagonal of the bounding box (D). |
stat |
a character vector with elements |
n |
integer between 2 and 100. Number of shots in each group. |
nGroups |
integer between 1 and 10. Number of groups when |
CIlevel |
confidence level (coverage probability) for the confidence interval. If one of |
collapse |
logical: should the list with CIs be simplified if possible? |
dstTarget |
a numerical value giving the distance to the target - used in MOA calculation. See |
conversion |
how to convert the measurement unit for distance to target to that of the (x,y)-coordinates in MOA calculation. Example |
Based on the lookup table DFdistr
with results from a Monte Carlo simulation. If the value of n
is not among those simulated (but is less than 100), a monotonic spline interpolation between the neighboring simulated values is used.
The CI is calculated based on implicit re-scaling by the Rayleigh sigma parameter. First, the tabulated CI boundaries are normalized to a range statistic with point estimate of 1 (via division by the tabulated mean). Then, the normalized CI boundaries are multiplied with the provided range statistic.
A named list with first component range_stat
. This is a matrix with columns ES
(extreme spread), FoM
(figure of merit), D
(bounding box diagonal). The second component CI
gives the corresponding confidence interval boundaries as a named list with components ES
, FoM
, D
.
Grubbs, F. E. (1964b). Statistical measures of accuracy for riflemen and missile engineers. Ann Arbor, ML: Edwards Brothers.
getRangeStat
,
range2sigma
getRangeStatCI(c(1, 2, 3),
stat=c("ES", "FoM", "D"),
n=10,
nGroups=1)
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