Estimation Instructions

RATS provides the following instructions for estimating regressions and other models:

AR1	Corrects for 1st-order serially correlated errors
BOXJENK	Estimates ARIMA, transfer function, and intervention models
CVMODEL	Covariance matrix modeling
CMOMENT	Computes cross-moment and correlation matrices
DDV	Estimates models with discrete dependent variables (logit, probit, etc.)
DLM	Dynamic linear modeling techniques
DSGE	Solves Dynamic Stochastic General Equilibrium Models
FIND	Simplex maximization or minimization
GARCH	Estimates ARCH, GARCH and related models (univariate and multivariate)
INSTRUMENTS	Sets the list of Instrumental variables
LDV	Estimates models with limited dependent variables (truncated, censored data)
LGT	Estimates logit models
LINREG	Estimates linear regressions
LQPROG	Solves linear and quadratic programming problems.
MCOV	Computes consistent covariance matrices
MAXIMIZE	General maximum-likelihood estimation
NLLS	Single-equation non-linear least squares estimation
NLPAR	Controls parameters for non-linear estimations
NLSYSTEM	Estimates non-linear system of equations
NNLEARN	Fits a neural net model
NNTEST	Generates output from an estimated neural net model
NONLIN	Sets free parameters for non-linear estimations
NPREG	Non-parametric regressions
PRBIT	Estimates probit models
PREGRESS	Panel data regressions, including fixed and random effects
RLS	Recursive least squares
RREG	Robust regressions
SWEEP	Regress one group of variables on another
STWISE	Estimates stepwise regressions
SUR	Estimates linear system of equations