Grocer Function
NAME
probit - probit regression
CALLING SEQUENCE
[rprobit]=probit(namey,arg1,...,argn)
PARAMETERS
Input
- grocer_namey = a time series, a real (nx1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes; all values should be 0 or 1.
-
argi = an argument that can be:
- a time series
- a real (nx1) vector
- a real (nxk) matrix
- a string equal to the name of a time series or a (nxk) real vector or matrix between quotes
- a list of such elements
- the string 'noprint' if the user doesn't want to display the results of the regression
Output
-
rprobit = a results tlist with
- rprobit('meth') = 'probit'
- rprobit('y') = y data vector
- rprobit('x') = x data matrix
- rprobit('nobs') = # observations
- rprobit('nvar') = # variables
- rprobit('beta') = bhat
- rprobit('yhat') = yhat
- rprobit('resid') = residuals
- rprobit('vcovar') = estimated variance-covariance matrix of beta
- rprobit('tstat') = t-stats
- rprobit('pvalue') = pvalue of the betas
- rprobit('r2mf') = = McFadden pseudo-Rē
- rprobit('rsqr') = = Estrella Rē
- rprobit('lratio') = LR-ratio test against intercept model
- rprobit('lik') = unrestricted Likelihood
- rprobit('zip') = # of 0's
- rprobit('one) = # of 1's
- rprobit('iter') = # of iterations
- rprobit('crit') = convergence criterion
- rprobit('namey') = name of the y variable
- rprobit('namex') = name of the x variables
- rprobit('prests') = boolean indicating the presence or absence of a time series in the regression
- rprobit('prescte') = %f (for printings)
- rprobit('bounds') = if there is a timeseries in the regression, the bounds of the regression
DESCRIPTION
Computes Probit Regression. Endogenous variable must be given first, as a vector, a ts, between quotes (if the user wants to keep the name of the variable in the tlist result and for the printings) or not. Exogenous variables are given after, in one of the formats authorized for the endogenous one, or in matrix format. The program displays on screen various results (coefficients, tstat, Rē, Durbin and Watson, first order autocorrelation of residuals,...) except if the user has entered the argument 'noprint' anywhere after the first argument.
EXAMPLES
1) r = probit('grade','cte','psi','tuce','gpa');
2) r = probit('grade','cte','psi','tuce','gpa', 'tol=sqrt(%eps)', 'noprint', 'maxit=200')
Example 1, taken from probit_d, shows the estimation of a probit model taken from Greene (1997).
Example 2 does the same, except that the options tol and maxit are set to non default values and that the results are not displayed.
AUTHOR
Eric Dubois 2002