| range2CEP | R Documentation |
Estimate the circular error probable (CEP) based on range statistics such as extreme spread, figure of merit, or the bounding box diagonal. This function assumes a circular bivariate normal shot distribution with 0 mean.
range2CEP(x, stat="ES", n=5, nGroups=1, CEPlevel=0.5, CIlevel=0.95,
collapse=TRUE, dstTarget, conversion)
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 |
CEPlevel |
a numerical vector with the coverage values for the CEP. |
CIlevel |
confidence level (coverage probability) for the CEP 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 form a Monte Carlo simulation. The Rayleigh sigma parameter is estimated using range2sigma, and then converted to CEP with qRayleigh.
If package shiny is installed, an interactive web app for this functionality can be run with runGUI("range").
A list with the calculated CEP values in one component, and the corresponding CIs in the other component.
CEP |
The calculated CEP values in the original measurement unit as well as in angular size measures. |
CEPCI |
The calculated CEP CIs in the original measurement unit as well as in angular size measures. |
Taylor, M. S., & Grubbs, F. E. (1975). Approximate Probability Distributions for the Extreme Spread (BRL-MR-2438). Aberdeen Proving Ground, MD: U.S. Ballistic Research Laboratory.
DFdistr,
range2sigma
qRayleigh
getCEP
es <- getMaxPairDist(DFscar17)$d
fom <- getBoundingBox(DFscar17)$FoM
d <- getBoundingBox(DFscar17)$diag
range2CEP(c(es, fom, d), stat=c("ES", "FoM", "D"),
n=nrow(DFscar17), nGroups=1, CEPlevel=0.5, CIlevel=0.9)
# compare with Rayleigh CEP estimate from using
# (x,y)-coordinates of all shots
getCEP(DFscar17, CEPlevel=0.5, type="Rayleigh")
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