powered by
Derives a three dimensional distribution of a turn angle, lift angle and step length, using the Freedman<U+2013>Diaconis rule for estimating the number of bins.
turnLiftStepHist( turn, lift, step, printDims = TRUE, rm.zeros = TRUE, maxBin = 25 )
numeric vector of turn angles
numeric vector of lift angles
numeric vector of step lengths
logical: should dimensions of tld-Cube be messaged?
logical: should combinations with zero probability be removed?
numeric scalar, maximum number of bins per dimension of the tld-cube.
A three dimensional histogram as data.frame
# NOT RUN { niclas <- track.properties.3d(niclas)[2:nrow(niclas), ] turnLiftStepHist(niclas$t, niclas$l, niclas$d) # }
Run the code above in your browser using DataLab