# Polyspherical Kernel Density Estimation

## Documentation for package ‘polykde’ version 1.1.7

- DESCRIPTION file.
- Package NEWS.

## Help Pages

polykde-package | 'polykde': Polyspherical Kernel Density Estimation
angles_to_polysph | Conversion between the angular and Cartesian coordinates of the polysphere
angles_to_sph | Conversion between the angular and Cartesian coordinates of the (hyper)sphere
angles_to_torus | Conversion between the angular and Cartesian coordinates of the torus
block_euler_ridge | Euler algorithms for polyspherical density ridge estimation
bw_cv_kre_polysph | Cross-validation bandwidth selection for polyspherical-on-scalar regression
bw_cv_polysph | Cross-validation bandwidth selection for polyspherical kernel density estimator
bw_lcv_min_epa | Minimum bandwidth allowed in likelihood cross-validation for Epanechnikov kernels
bw_mrot_polysph | Marginal rule-of-thumb bandwidth selection for polyspherical kernel density estimator
bw_rot_polysph | Rule-of-thumb bandwidth selection for polyspherical kernel density estimator
b_d | Polyspherical kernel moments and efficiencies
clean_euler_ridge | Clean ridge points coming from spurious fits
comp_ind_dj | Index of spheres on a polysphere
curv_vmf_polysph | Curvature of a polyspherical von Mises-Fisher density
c_kern | Kernels on the sphere and their derivatives
dist_polysph | Polyspherical distance
dist_polysph_cross | Polyspherical distance
dist_polysph_matrix | Polyspherical distance
d_mvmf_polysph | Density of the product of von Mises-Fisher distributions on the polysphere
d_unif_polysph | Density of the uniform distribution on the polysphere
d_vmf_polysph | Density of the product of von Mises-Fisher distributions on the polysphere
eff_kern | Polyspherical kernel moments and efficiencies
euler_ridge | Euler algorithms for polyspherical density ridge estimation
fib_latt | Fibonacci lattice on the sphere
grad_hess_kde_polysph | Gradient and Hessian of the polyspherical kernel density estimator
grad_L | Kernels on the sphere and their derivatives
hammer_to_sph | Map Cartesian coordinates into Hammer projection
hess_L | Kernels on the sphere and their derivatives
hippocampus | Skeletal representation of hippocampus shapes
hom_test_polysph | Homogeneity test for several polyspherical samples
index_ridge | Index a ridge curve, creating the Smoothed and Indexed Estimated Ridge (SIER)
interp_polysph | Interpolation on the polysphere
kde_polysph | Polyspherical kernel density estimator
kernel | Kernels on the sphere and their derivatives
kre_polysph | Local polynomial estimator for polyspherical-on-scalar regression
L | Kernels on the sphere and their derivatives
log_cv_kde_polysph | Cross-validation for the polyspherical kernel density estimator
parallel_euler_ridge | Euler algorithms for polyspherical density ridge estimation
polykde | 'polykde': Polyspherical Kernel Density Estimation
polylog_minus_exp_mu | Polylogarithm function with negative argument
polysph_to_angles | Conversion between the angular and Cartesian coordinates of the polysphere
proj_grad_kde_polysph | Projected gradient of the polyspherical kernel density estimator
proj_polysph | Projection onto the polysphere
r_g_kern | Sample from the angular kernel density
r_kde_polysph | Sample from polyspherical kernel density estimator
r_kern_polysph | Sample kernel-distributed polyspherical data
r_mvmf_polysph | Sample mixtures of von Mises-Fisher distributed polyspherical data
r_path_s1r | Samplers of one-dimensional modes of variation for polyspherical data
r_path_s2r | Samplers of one-dimensional modes of variation for polyspherical data
r_unif_polysph | Sample uniform polyspherical data
r_vmf_polysph | Sample von Mises-Fisher distributed polyspherical data
softplus | Stable computation of the softplus function
sph_to_angles | Conversion between the angular and Cartesian coordinates of the (hyper)sphere
sph_to_hammer | Map Cartesian coordinates into Hammer projection
torus_to_angles | Conversion between the angular and Cartesian coordinates of the torus
view_srep | s-rep viewer
v_d | Polyspherical kernel moments and efficiencies