aldvmm.init {aldvmm}  R Documentation 
Creating Initial Values
Description
aldvmm.init
creates initial values for the minimization of the negative loglikelihood
returned by
aldvmm.ll
using
optimr
.
Usage
aldvmm.init(
X,
y,
psi,
ncmp,
dist,
init.method,
init.est,
init.lo,
init.hi,
optim.method,
optim.control = list(),
optim.grad,
lcoef,
lcpar,
lcmp
)
Arguments
X 
a list of design matrices returned by

y 
a numeric vector of observed outcomes from complete observations in

psi 
a numeric vector of minimum and maximum possible utility values
smaller than or equal to 1 (e.g. 
ncmp 
a numeric value of the number of components that are mixed. The
default value is 2. A value of 1 represents a tobit model with a gap
between 1 and the maximum value in 
dist 
an optional character value of the distribution used in the
components. In this release, only the normal distribution is
available, and the default value is set to 
init.method 
an optional character value indicating the method for
obtaining initial values. The following values are available:

init.est 
an optional numeric vector of userdefined initial values.
Userdefined initial values override the 
init.lo 
an optional numeric vector of userdefined lower limits for
constrained optimization. When 
init.hi 
an optional numeric vector of userdefined upper limits for
constrained optimization. When 
optim.method 
an optional character value of one of the following

optim.control 
an optional list of

optim.grad 
an optional logical value indicating if an analytical
gradient should be used in

lcoef 
a character vector of length 2 with labels of objects including
regression coefficients of component distributions (default 
lcpar 
a character vector with the labels of objects including
constant parameters of component distributions (e.g. the standard
deviation of the normal distribution). The length of 
lcmp 
a character value representing a stub (default 
Details
'init.method'
accepts four methods for generating initial
values: "zero"
, "random"
, "constant"
, "sann"
.
The method "zero"
sets initial values of all parameters to 0. The
method "random"
draws random starting values from a standard normal
distribution. The method "constant"
estimates a constantonly
model and uses estimates as initial values for intercepts and constant
distribution parameters and 0 for all other parameters. The method
"sann"
estimates the full model using the simulated annealing
optimization method and uses all parameter estimates as initial values.
When userspecified initial values are supplied in 'init.est'
, the
argument 'init.method'
is ignored.
By default, aldvmm
performs unconstrained optimization with upper and lower limits at
Inf
and Inf
. When userdefined lower and upper limits are
supplied to 'init.lo'
and/or 'inithi'
, these default limits
are replaced with the userspecified values, and the method
"LBFGSB"
is used for boxconstrained optimization instead of the
user defined 'optim.method'
. It is possible to only set either
maximum or minimum limits. When initial values supplied to
'init.est'
or from default methods lie outside the limits, the
infeasible values will be set to the limits using the function
bmchk
.
Value
aldvmm.init
returns a list with the following objects.
est 
a numeric vector of initial values of parameters. 
lo 
a numeric vector of lower limits of parameters. 
hi 
a numeric vector of upper limits of parameters. 