choose.cluster |
Choosing the cluster which is closest to a specified point |
contour |
Plot clusters with different colors for two dimensional data overlayed on the contours of the original data. |
contour.hmac |
Plot clusters with different colors for two dimensional data overlayed on the contours of the original data. |
cta20 |
Two dimensional data in original and log scale |
cta20.hmac |
Two dimensional data in original and log scale |
disc2d |
Two and three dimensional data representing two half discs |
disc2d.hmac |
Two and three dimensional data representing two half discs |
disc3d |
Two and three dimensional data representing two half discs |
disc3d.hmac |
Two and three dimensional data representing two half discs |
dmvnorm |
Calculate Density of Multivariate Normal for diagonal covariance |
findmid |
Find the mid point of memberships of each cluster |
hard.hmac |
Plot clusters with different colors. |
hmac |
Perform Modal Clustering in serial mode only |
khat |
Calculate the smoothing paramters for implementation of Modal Clustering. |
khat.inv |
Calculate the smoothing paramters for implementation of Modal Clustering. |
logcta20 |
Two dimensional data in original and log scale |
logcta20.hmac |
Two dimensional data in original and log scale |
modalclust |
Main function for performing Modal Clusters either parallel or serial mode. |
mydmvnorm |
Calculate Density of Multivariate Normal for diagonal covariance |
oned |
One dimensional data with two main clusters |
oned.hmac |
One dimensional data with two main clusters |
phmac |
Main function for performing Modal Clusters either parallel or serial mode. |
plot |
Plots of heierarchical tree for a 'hmac' object |
plot.hmac |
Plots of heierarchical tree for a 'hmac' object |
sdofnorm |
Calculate the smoothing paramters for implementation of Modal Clustering. |
soft.hmac |
Plot soft clusters from Modal Clustering output |
summary |
Summary of HMAC output |
summary.hmac |
Summary of HMAC output |