groupSpread(xy, plots = TRUE, level = 0.95,
CEPtype = c('Rayleigh', 'Grubbs', 'RAND'),
sigmaType=c('Rayleigh', 'Gauss'),
dstTarget = 100, conversion = 'm2cm')
## S3 method for class 'data.frame':
groupSpread(xy, plots = TRUE, level = 0.95,
CEPtype = c('Rayleigh', 'Grubbs', 'RAND'),
sigmaType=c('Rayleigh', 'Gauss'),
dstTarget = 100, conversion = 'm2cm')
## S3 method for class 'default':
groupSpread(xy, plots = TRUE, level = 0.95,
CEPtype = c('Rayleigh', 'Grubbs', 'RAND'),
sigmaType=c('Rayleigh', 'Gauss'),
dstTarget = 100, conversion = 'm2cm')X, Y or Point.X, Point.Y as well as Aim.XgetCEP.getMOA.getMOA.covMcd using the MCD algorithm.
In addition to the numerical results listed below, this function produces the following diagrams:
level\%-confidence ellipse - the latter also based on a robust estimate for the covariance matrixgetDistToCtr,
getMaxPairDist,
getBoundingBox,
getMinBBox,
getMinCircle,
getConfEll,
getCEP,
getRayParam,
getMOA,
hist,
boot,
boot.ci,
kernel,
covMcd,# coordinates given by a suitable data frame
res <- groupSpread(DFtalon, CEPtype=c("Rayleigh", "Grubbs"), level=0.95,
sigmaType='Rayleigh', dstTarget=10, conversion='m2mm')
names(res)
res$sdXYrob
res$distToCtr
res$maxPairDist
res$CEP
# coordinates given by a matrix
xy <- matrix(round(rnorm(200, 0, 5), 2), ncol=2)
groupSpread(xy, level=0.5, dstTarget=25, conversion='m2cm')Run the code above in your browser using DataLab