By default, random variables are generated by mapping isotropic Gaussian distributions on the tangent space back to the manifold using the exponential map
rmfd(mfd, n, dimIntrinsic, ...)# S3 method for default
rmfd(
mfd,
n,
dimIntrinsic,
p,
dist = c("norm", "unif", "exp"),
totalVar = 1,
...
)
A matrix with n columns, each containing a random sample on the manifold
A manifold object created by createM
Sample size
The intrinsic dimension of the target manifold
Passed into specific methods
Optionally, specify the base point of the tangent space, on which random tangent vectors will be generated. Default to the origin of `mfd`.
Either a string or a function, describing the distributions. If it is character, then independent univariate r.v. following that distribution with total variance 1 is generated on the tangent space. If it is a function, it should specify the generation of the samples on the tangent space _coordinates_ (with dimension dimIntrinsic), and it must return a matrix for which the columns are the coordinates. Then it will be mapped to the tangent space at the origin and then to the manifold.
Total variance (sum of diagonal of the covariance matrix) of the tangent random vector
rmfd(default): Default method