ParamNMoE-class: A Reference Class which contains parameters of a NMoE model.
In meteorits: Mixture-of-Experts Modeling for Complex Non-Normal Distributions

ParamNMoE contains all the parameters of a NMoE model.

X: Numeric vector of length n representing the covariates/inputs x_{1},…,x_{n}.
Y: Numeric vector of length n representing the observed response/output y_{1},…,y_{n}.
n: Numeric. Length of the response/output vector Y.
K: The number of experts.
p: The order of the polynomial regression for the experts.
q: The order of the logistic regression for the gating network.
alpha: Parameters of the gating network. α = (α_{1},…,α_{K-1}) is a matrix of dimension (q + 1, K - 1), with q the order of the logistic regression for the gating network. q is fixed to 1 by default.
beta: Polynomial regressions coefficients for each expert. β = (β_{1},…,β_{K}) is a matrix of dimension (p + 1, K), with p the order of the polynomial regression. p is fixed to 3 by default.
sigma2: The variances for the K mixture components (matrix of size (1, K)).
df: The degree of freedom of the NMoE model representing the complexity of the model.

initParam(segmental = FALSE)

Method to initialize parameters alpha, beta and sigma2.

If segmental = TRUE then alpha, beta and sigma2 are initialized by clustering the response Y uniformly into K contiguous segments. Otherwise, alpha, beta and sigma2 are initialized by clustering randomly the response Y into K segments.