Command Reference : Command Reference

 binary
Estimate binary dependent variable models.
Estimates models where the binary dependent variable Y is either zero or one (probit, logit, gompit).
Syntax
binary(options) y x1 [x2 x3 ...]
binary(options) specification
Options

 d=arg (default=“n”) Specify likelihood: normal likelihood function, probit (“n”), logistic likelihood function, logit (“l”), Type I extreme value likelihood function, 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 - default).(Applicable when non-legacy “optmethod=”.) h Huber-White quasi-maximum likelihood (QML) standard errors and covariances.(Legacy option applicable when “optmethod=legacy”). g GLM 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 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.
Examples
To estimate a logit model of Y using a constant, WAGE, EDU, and KIDS, and computing Huber-White standard errors, you may use the command:
binary(d=l,cov=huber) y c wage edu kids
Note that this estimation uses the default global optimization options. The commands:
param c(1) .1 c(2) .1 c(3) .1
binary(s) y c x2 x3
estimate a probit model of Y on a constant, X2, and X3, using the specified starting values. The commands:
coef beta_probit = @coefs
matrix cov_probit = @coefcov
store the estimated coefficients and coefficient covariances in the coefficient vector BETA_PROBIT and matrix COV_PROBIT.
Cross-references
See “Binary Dependent Variable Models” for additional discussion.
See Equation::binary for the corresponding equation method.