## S3 method for class 'SO3':
mean(x, type = "projected",
epsilon = 1e-05, maxIter = 2000, ...) ## S3 method for class 'Q4':
mean(x, type = "projected",
epsilon = 1e-05, maxIter = 2000, ...)
type
option. For a sample of $n$ rotations in
matrix form $\bm{R}_i\in SO(3), i=1,2,\dots,n$, the mean-type estimator is defined
as $$\widehat{\bm{S}}=argmin_{\bm{S}\in
SO(3)}\sum_{i=1}^nd^2(\bm{R}_i,\bm{S})$$ where $d$ is the Riemannian or Euclidean
distance. For more on the projected mean see
Moakher (2002) and for the geometric mean see
Manton (2004). For the projected mean from a
quaternion point of view see Tyler (1981).Manton JH (2004). "A globally convergent numerical algorithm for computing the centre of mass on compact Lie groups." In Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th, volume 3, pp. 2211-2216. IEEE.
Tyler DE (1981). "Asymptotic inference for eigenvectors." The Annals of Statistics, pp. 725-736.
median.SO3
Rs<-ruars(20,rvmises,kappa=0.01)
mean(Rs)
Qs<-Q4(Rs)
mean(Qs)
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