ModelMixRHLP represents an estimated mixture of RHLP model.
A ParamMixRHLP object. It contains the estimated values of the parameters.
A StatMixRHLP object. It contains all the statistics associated to the MixRHLP model.
plot(what = c("estimatedsignal", "regressors", "loglikelihood"), ...)
The type of graph requested:
"estimatedsignal" = Estimated signal (field
Ey of class StatMixRHLP).
"regressors" = Polynomial regression components
pi_jkr of class
"loglikelihood" = Value of the log-likelihood for
each iteration (field
stored_loglik of class
Other graphics parameters.
By default, all the above graphs are produced.
summary(digits = getOption("digits"))
The number of significant digits to use when printing.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
data(toydataset) # Let's fit a mixRHLP model on a dataset containing 2 clusters: data <- toydataset[1:190,1:21] x <- data$x Y <- t(data[,2:ncol(data)]) mixrhlp <- cemMixRHLP(X = x, Y = Y, K = 2, R = 2, p = 1, verbose = TRUE) # mixrhlp is a ModelMixRHLP object. It contains some methods such as 'summary' and 'plot' mixrhlp$summary() mixrhlp$plot() # mixrhlp has also two fields, stat and param which are reference classes as well # Log-likelihood: mixrhlp$stat$loglik # Parameters of the polynomial regressions: mixrhlp$param$beta
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.