ModelSNMoE-class: A Reference Class which represents a fitted SNMoE model.
In meteorits: Mixture-of-Experts Modeling for Complex Non-Normal Distributions

Description Fields Methods See Also Examples

ModelSNMoE represents an estimated SNMoE model.

param: A ParamSNMoE object. It contains the estimated values of the parameters.
stat: A StatSNMoE object. It contains all the statistics associated to the SNMoE model.

plot(what = c("meancurve", "confregions", "clusters", "loglikelihood"), ...)

Plot method.

what

The type of graph requested:

"meancurve" = Estimated mean and estimated experts means given the input X (fields Ey and Ey_k of class StatSNMoE).
"confregions" = Estimated mean and confidence regions. Confidence regions are computed as plus and minus twice the estimated standard deviation (the squarre root of the field Vary of class StatSNMoE).
"clusters" = Estimated experts means (field Ey_k) and hard partition (field klas of class StatSNMoE).
"loglikelihood" = Value of the log-likelihood for each iteration (field stored_loglik of class StatSNMoE).

...

Other graphics parameters.

By default, all the graphs mentioned above are produced.

summary(digits = getOption("digits"))

Summary method.

digits: The number of significant digits to use when printing.

ParamSNMoE, StatSNMoE

data(tempanomalies)
x <- tempanomalies$Year
y <- tempanomalies$AnnualAnomaly

snmoe <- emSNMoE(X = x, Y = y, K = 2, p = 1, verbose = TRUE)

# snmoe is a ModelSNMoE object. It contains some methods such as 'summary' and 'plot'
snmoe$summary()
snmoe$plot()

# snmoe has also two fields, stat and param which are reference classes as well

# Log-likelihood:
snmoe$stat$loglik

# Parameters of the polynomial regressions:
snmoe$param$beta