ssmn.est {ssmn} | R Documentation |
EM algorithm for Skew Scale Mixtures of Normal Distributions
Description
Performs the EM algorithm and envelope for regression models using Skew Scale Mixtures of Normal Distributions
Usage
ssmn(y, X, family="sn", method="EM", error = 1e-6, maxit=1000, show.envelope=FALSE)
envel(y,X, theta, family="sn", alpha=0.05)
Arguments
y |
the response vector of length |
X |
the matrix of explanatory variables of dimension |
family |
its defines the distribution to ber used: sn, stn, ssl, scn or sep. |
method |
the method to calculate the maximum likelihood estimates: EM algorithm or direct maximum likelihood estimates via Newton-Raphson. |
maxit |
Maximum number of iterations. |
error |
accuracy the convergence maximum error. |
show.envelope |
TRUE or FALSE. Indicates if envelope graph should be built for the fitted model. Default is FALSE. |
alpha |
1 - alpha is level of confidence. |
theta |
Estimated parameter vector |
Value
The function returns a list with 8 elements detailed as
iter |
number of iterations. |
tetha |
estimated parameter vector. |
SE |
Standard Error estimates. |
table |
Table containing the inference for the estimated parameters. |
loglik |
Log-likelihood value. |
AIC |
Akaike information criterion. |
BIC |
Bayesian information criterion. |
time |
processing time. |