Usage
msn.dev(param, X, y, freq, trace=FALSE)
msn.dev.grad(param, X, y, freq, trace=FALSE)
msn.moment.fit(y)
mst.dev(param, X, y, freq, fixed.df=NA, trace=FALSE)
mst.dev.grad(param, X, y, freq, fixed.df=NA, trace=FALSE)
num.deriv1(x, FUN, ...)
num.deriv2(x, FUN, ...)
st.dev.fixed(free.param, X, y, freq, trace=FALSE, fixed.comp=NA, fixed.values=NA)
sn.dev(cp, X, y, trace=FALSE)
sn.dev.gh(cp, X, y, trace=FALSE, hessian=FALSE)
sn.logL.grouped(param, breaks, freq, trace=FALSE)
solvePD(x)
st.logL.grouped(param, breaks, freq, trace=FALSE)
sn.SFscore(shape, z, trace=FALSE)
st.SFscore(shape, df, z, trace=FALSE)
Arguments
param,cp, coefficients, shape
a numeric vector of parameter values.
X
a matrix of explanatory variables; must have col(X) equal to
length(y). Missing values (NA) are not allowed.
If X is missing, a one-column matrix of 1's is created.
x,y,z
a numeric vector or matrix, depending on the context.
freq
a vector of frequencies.
trace
logical value which controls printing of the algorithm convergence.
If trace=TRUE, details are printed. Default value is FALSE.
free.param
a vector of suitably re-parametrized parameters, not to be kept fixed during
iteration.
fixed.comp
a vector containing the subset of the parameters for which the
profile log-likelihood function is required; it can be of length 1 or 2.
fixed.values
a numeric vector of values or a matrix with two columns, giving the
range spanned by the selected parameters.
fixed.df
a scalar value contaning the degrees of freedom (df), if these must
be taked as fixed, or NA (deafult value) if df is a parameter
to be estimated.
breaks
a vector contaning the cut points of the groups, given
in ascending order. The last value can be Inf, the
first one can be -Inf