Command Reference : Command Reference
  
 
ordered
Estimation of ordered dependent variable models.
Syntax
equation name.ordered(options) y x1 [x2 x3 ...]
equation name.ordered(options) specification
Options
 
d=arg (default=“n”)
Specify likelihood: normal likelihood function, ordered probit (“n”), logistic likelihood function, ordered logit (“l”), Type I extreme value likelihood function, ordered Gompit (“x”).
optmethod = arg
Optimization method: “bfgs” (BFGS); “newton” (Newton-Raphson), “opg” or “bhhh” (OPG or BHHH), “legacy” (EViews legacy).
Newton-Raphson is the default method.
optstep = arg
 
Step method: “marquardt” (Marquardt); “dogleg” (Dogleg); “linesearch” (Line search).
Marquardt is the default method.
cov=arg
Covariance method: “ordinary” (default method based on inverse of the estimated information matrix), “huber” or “white” (Huber-White sandwich method)., “glm” (GLM method)..
covinfo = arg
Information matrix method: “opg” (OPG); “hessian” (observed Hessian).
(Applicable when non-legacy “optmethod=”.)
h
Huber-White quasi-maximum likelihood (QML) standard errors and covariances.
(Legacy option Applicable when “optmethod=legacy”).
m=integer
Set maximum number of iterations.
c=scalar
Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled coefficients. The criterion will be set to the nearest value between 1e-24 and 0.2.
s
Use the current coefficient values in “C” as starting values (see also param).
s=number
Specify a number between zero and one to determine starting values as a fraction of preliminary EViews default values (out of range values are set to “s=1”).
showopts / ‑showopts
[Do / do not] display the starting coefficient values and estimation options in the estimation output.
coef=arg
Specify the name of the coefficient vector (if specified by list); the default behavior is to use the “C” coefficient vector.
prompt
Force the dialog to appear from within a program.
p
Print results.
If you choose to employ user specified starting values, the parameters corresponding to the limit points must be in ascending order.
Examples
ordered(d=l,cov=huber) y c wage edu kids
estimates an ordered logit model of Y on a constant, WAGE, EDU, and KIDS with QML standard errors. This command uses the default quadratic hill climbing algorithm.
param c(1) .1 c(2) .2 c(3) .3 c(4) .4 c(5).5
equation eq1.binary(s) y c x z
coef betahat = @coefs
estimates an ordered probit model of Y on a constant, X, and Z from the specified starting values. The estimated coefficients are then stored in the coefficient vector BETAHAT.
Cross-references
See “Ordered Dependent Variable Models” for additional discussion.
See also binary.
See Equation::ordered for the equivalent equation object command.