S4 class for standard deviation. It inherits from EL class.
optim
A list of the following optimization results:
par
A numeric vector of the specified parameters.
lambda
A numeric vector of the Lagrange multipliers of the dual
problem corresponding to par
.
iterations
A single integer for the number of iterations performed.
convergence
A single logical for the convergence status.
cstr
A single logical for whether constrained EL optimization is
performed or not.
logp
A numeric vector of the log probabilities of the empirical likelihood.
logl
A single numeric of the empirical log-likelihood.
loglr
A single numeric of the empirical log-likelihood ratio.
statistic
A single numeric of minus twice the empirical log-likelihood ratio with an asymptotic chi-square distribution.
df
A single integer for the degrees of freedom of the statistic.
pval
A single numeric for the \(p\)-value of the statistic.
nobs
A single integer for the number of observations.
npar
A single integer for the number of parameters.
weights
A numeric vector of the re-scaled weights used for the model fitting.
coefficients
A numeric vector of the maximum empirical likelihood estimates of the parameters.
method
A single character for the method dispatch in internal functions.
data
A numeric matrix of the data for the model fitting.
control
An object of class ControlEL constructed by
el_control()
.
showClass("SD")
#> Class "SD" [package "melt"]
#>
#> Slots:
#>
#> Name: optim logp logl loglr statistic
#> Class: list numeric numeric numeric numeric
#>
#> Name: df pval nobs npar weights
#> Class: integer numeric integer integer numeric
#>
#> Name: coefficients method data control
#> Class: numeric character ANY ControlEL
#>
#> Extends: "EL"