Density Estimation via Model-Based Clustering
Produces a density estimate for each data point using a Gaussian finite
mixture model from Mclust.
densityMclust(data, ..., plot = TRUE)
data |
A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables. |
... |
Additional arguments for the |
plot |
A logical value specifying if the estimated density should be
plotted. For more contols on the resulting graph see the associated
|
An object of class densityMclust, which inherits from
Mclust. This contains all the components described in
Mclust and the additional element:
density |
The density evaluated at the input |
Revised version by Luca Scrucca based on the original code by C. Fraley and A.E. Raftery.
Scrucca L., Fop M., Murphy T. B. and Raftery A. E. (2016) mclust 5: clustering, classification and density estimation using Gaussian finite mixture models, The R Journal, 8/1, pp. 289-317.
Fraley C. and Raftery A. E. (2002) Model-based clustering, discriminant analysis and density estimation, Journal of the American Statistical Association, 97/458, pp. 611-631.
Fraley C., Raftery A. E., Murphy T. B. and Scrucca L. (2012) mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.
dens <- densityMclust(faithful$waiting)
summary(dens)
summary(dens, parameters = TRUE)
plot(dens, what = "BIC", legendArgs = list(x = "topright"))
plot(dens, what = "density", data = faithful$waiting)
dens <- densityMclust(faithful, modelNames = "EEE", G = 3, plot = FALSE)
summary(dens)
summary(dens, parameters = TRUE)
plot(dens, what = "density", data = faithful,
drawlabels = FALSE, points.pch = 20)
plot(dens, what = "density", type = "hdr")
plot(dens, what = "density", type = "hdr", prob = c(0.1, 0.9))
plot(dens, what = "density", type = "hdr", data = faithful)
plot(dens, what = "density", type = "persp")
dens <- densityMclust(iris[,1:4], G = 2)
summary(dens, parameters = TRUE)
plot(dens, what = "density", data = iris[,1:4],
col = "slategrey", drawlabels = FALSE, nlevels = 7)
plot(dens, what = "density", type = "hdr", data = iris[,1:4])
plot(dens, what = "density", type = "persp", col = grey(0.9))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.