cdens |
Component Density for Parameterized MVN Mixture Models |
cdensE |
Component Density for a Parameterized MVN Mixture Model |
cdensEEE |
Component Density for a Parameterized MVN Mixture Model |
cdensEEI |
Component Density for a Parameterized MVN Mixture Model |
cdensEEV |
Component Density for a Parameterized MVN Mixture Model |
cdensEII |
Component Density for a Parameterized MVN Mixture Model |
cdensEVI |
Component Density for a Parameterized MVN Mixture Model |
cdensV |
Component Density for a Parameterized MVN Mixture Model |
cdensVEI |
Component Density for a Parameterized MVN Mixture Model |
cdensVEV |
Component Density for a Parameterized MVN Mixture Model |
cdensVII |
Component Density for a Parameterized MVN Mixture Model |
cdensVVI |
Component Density for a Parameterized MVN Mixture Model |
cdensVVV |
Component Density for a Parameterized MVN Mixture Model |
chevron |
Simulated minefield data |
classError |
Classification error. |
clPairs |
Pairwise Scatter Plots showing Classification |
coordProj |
Coordinate projections of multidimensional data modeled by an MVN mixture. |
cross |
Simulated Cross Data |
cv1EMtrain |
Select discriminant models using cross validation |
em |
EM algorithm starting with E-step for parameterized Gaussian mixture models. |
EMclust |
BIC for Model-Based Clustering |
emControl |
Set control values for use with the EM algorithm. |
emE |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emEEE |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emEEI |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emEEV |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emEII |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emEVI |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emV |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emVEI |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emVEV |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emVII |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emVVI |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
emVVV |
EM algorithm starting with E-step for a parameterized Gaussian mixture model. |
estep |
E-step for parameterized Gaussian mixture models. |
estepE |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEEE |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEEI |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEEV |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEII |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEVI |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepV |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVEI |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVEV |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVII |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVVI |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVVV |
E-step in the EM algorithm for a parameterized Gaussian mixture model. |
map |
Classification given Probabilities |
mapClass |
Correspondence between classifications. |
Mclust |
Model-Based Clustering |
mclust1Dplot |
Plot one-dimensional data modeled by an MVN mixture. |
mclust2Dplot |
Plot two-dimensional data modelled by an MVN mixture. |
mclustBIC |
BIC for Model-Based Clustering |
mclustDA |
MclustDA discriminant analysis. |
mclustDAtest |
MclustDA Testing |
mclustDAtrain |
MclustDA Training |
mclustModel |
Best model based on BIC. |
mclustModelNames |
MCLUST Model Names |
mclustOptions |
Set default values for use with MCLUST. |
mclustVariance |
Template for variance specification for parameterized Gaussian mixture models. |
me |
EM algorithm starting with M-step for parameterized MVN mixture models. |
meE |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meEEE |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meEEI |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meEEV |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meEII |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meEVI |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meV |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meVEI |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meVEV |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meVII |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meVVI |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
meVVV |
EM algorithm starting with M-step for a parameterized Gaussian mixture model. |
mstep |
M-step for parameterized Gaussian mixture models. |
mstepE |
M-step for a parameterized Gaussian mixture model. |
mstepEEE |
M-step for a parameterized Gaussian mixture model. |
mstepEEI |
M-step for a parameterized Gaussian mixture model. |
mstepEEV |
M-step for a parameterized Gaussian mixture model. |
mstepEII |
M-step for a parameterized Gaussian mixture model. |
mstepEVI |
M-step for a parameterized Gaussian mixture model. |
mstepV |
M-step for a parameterized Gaussian mixture model. |
mstepVEI |
M-step for a parameterized Gaussian mixture model. |
mstepVEV |
M-step for a parameterized Gaussian mixture model. |
mstepVII |
M-step for a parameterized Gaussian mixture model. |
mstepVVI |
M-step for a parameterized Gaussian mixture model. |
mstepVVV |
M-step for a parameterized Gaussian mixture model. |
mvn |
Univariate or Multivariate Normal Fit |
mvnX |
Univariate or Multivariate Normal Fit |
mvnXII |
Univariate or Multivariate Normal Fit |
mvnXXI |
Univariate or Multivariate Normal Fit |
mvnXXX |
Univariate or Multivariate Normal Fit |
sigma2decomp |
Convert mixture component covariances to decomposition form. |
sim |
Simulate from Parameterized MVN Mixture Models |
simE |
Simulate from a Parameterized MVN Mixture Model |
simEEE |
Simulate from a Parameterized MVN Mixture Model |
simEEI |
Simulate from a Parameterized MVN Mixture Model |
simEEV |
Simulate from a Parameterized MVN Mixture Model |
simEII |
Simulate from a Parameterized MVN Mixture Model |
simEVI |
Simulate from a Parameterized MVN Mixture Model |
simV |
Simulate from a Parameterized MVN Mixture Model |
simVEI |
Simulate from a Parameterized MVN Mixture Model |
simVEV |
Simulate from a Parameterized MVN Mixture Model |
simVII |
Simulate from a Parameterized MVN Mixture Model |
simVVI |
Simulate from a Parameterized MVN Mixture Model |
simVVV |
Simulate from a Parameterized MVN Mixture Model |
summary.mclustBIC |
Summary Function for model-based clustering. |
summary.mclustDAtest |
Classification and posterior probability from mclustDAtest. |
summary.mclustDAtrain |
Models and classifications from mclustDAtrain |
summary.mclustModel |
Summary Function for MCLUST Models |
summaryMclustBIC |
Summary Function for model-based clustering. |
summaryMclustBICn |
Summary Function for model-based clustering. |
surfacePlot |
Density or uncertainty surface for bivariate mixtures. |