| LM-class | R Documentation |
S4 class for linear models with empirical likelihood. It inherits from CEL class.
The overall test involves a constrained optimization problem. All
the parameters except for the intercept are constrained to zero. The
optim slot contains the results. When there is no intercept, all
parameters are set to zero, and the results need to be understood in terms
of EL class since no constrained optimization is involved.
Once the solution is found, the log probabilities (logp) and the
(constrained) empirical likelihood values (logl, loglr, statistic)
readily follow, along with the degrees of freedom (df) and the
p-value (pval). The significance tests for each parameter also
involve constrained optimization problems where only one parameter is
constrained to zero. The sigTests slot contains the results.
formula(LM): Extracts the symbolic model formula used in el_lm() or
el_glm().
sigTestsA list of the following results of significance tests:
statistic A numeric vector of minus twice the (constrained) empirical
log-likelihood ratios with asymptotic chi-square distributions.
iterations An integer vector for the number of iterations performed for
each parameter.
convergence A logical vector for the convergence status of each
parameter.
callA matched call.
termsA terms object used.
miscA list of various outputs obtained from the model fitting process. They are used in other generics and methods.
optimA list of the following optimization results:
par A numeric vector of the solution to the (constrained) optimization
problem.
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.
logpA numeric vector of the log probabilities of the (constrained) empirical likelihood.
loglA single numeric of the (constrained) empirical log-likelihood.
loglrA single numeric of the (constrained) empirical log-likelihood ratio.
statisticA single numeric of minus twice the (constrained) empirical log-likelihood ratio with an asymptotic chi-square distribution.
dfA single integer for the degrees of freedom of the statistic.
pvalA single numeric for the p-value of the statistic.
nobsA single integer for the number of observations.
nparA single integer for the number of parameters.
weightsA numeric vector of the re-scaled weights used for the model fitting.
coefficientsA numeric vector of the maximum empirical likelihood estimates of the parameters.
methodA single character for the method dispatch in internal functions.
dataA numeric matrix of the data for the model fitting.
controlAn object of class ControlEL constructed by
el_control().
showClass("LM")
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