Object Reference : Object View and Procedure Reference : Equation : varsel : General options
  
 
varsel
Estimation using variable selection.
Syntax
eq_name.varsel(options) y x1 [x2 x3 ...] @ z1 z2 z3
Specify the dependent variable followed by a list of variables to be included in the regression, but not part of the search routine, followed by an “@” symbol and a list of variables to be part of the search routine. If no included variables are required, simply follow the dependent variable with an “@” symbol and the list of search variables.
Options
 
method = arg
Stepwise regression method: “stepwise” (default), “uni” (uni-directional), “swap” (swapwise), “comb” (combinatorial), “gets” (auto-search/GETS), “lasso” (Lasso).
nvars = int
Set the number of search regressors. Required for swapwise and combinatorial methods, optional for uni-directional and stepwise methods.
w=arg
Weight series or expression.
Note: we recommend that, absent a good reason, you employ the default settings Inverse std. dev. weights (“wtype=istdev”) with EViews default scaling (“wscale=eviews”) for backward compatibility with versions prior to EViews 7.
wtype=arg (default=“istdev”)
Weight specification type: inverse standard deviation (“istdev”), inverse variance (“ivar”), standard deviation (“stdev”), variance (“var”).
wscale=arg
Weight scaling: EViews default (“eviews”), average (“avg”), none (“none”).
The default setting depends upon the weight type: “eviews” if “wtype=istdev”, “avg” for all others.
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 estimation results.
Stepwise and uni-directional method options
 
back
Set stepwise or uni-directional method to run backward. If omitted, the method runs forward.
tstat
Use t-statistic values as a stopping criterion. (default uses p-values).
ftol=number (default = 0.5)
Set forward stopping criterion value.
btol=number (default = 0.5)
Set backward stopping criterion value.
fmaxstep=int (default = 1000)
Set the maximum number of steps forward.
bmaxstep=int (default = 1000)
Set the maximum number of steps backward.
tmaxstep=int (default = 2000)
Set the maximum total number of steps.
Swapwise method options
 
minr2
Use minimum R-squared increments. (Default uses maximum R-squared increments.)
Combinatorial method options
 
force
Suppress the warning message issued when a large number of regressions will be performed.
Auto-search/GETS method options
 
pval=number (default = 0.05)
Set the terminal condition p-value used to determine the stopping point of each search path
nolm
Do not perform AR LM diagnostic test.
arpval=number (default = 0.025)
Set p-value used in AR LM diagnostic test.
arlags=int (default = 1)
Set number of lags used in AR LM diagnostic test.
noarch
Do not perform ARCH LM diagnostic test.
archpval=number (default = 0.025)
Set p-value used in ARCH LM diagnostic test.
archlags=int (default = 1)
Set number of lags used in ARCH LM diagnostic test.
nojb
Do not perform Jarque-Bera normality diagnostic test.
jbpval=number (default = 0.025)
Set p-value used in Jarque-Bera normality diagnostic test.
nopet
Do not perform Parsimonious Encompassing diagnostic test.
petpval=number (default = 0.025)
Set p-value used in Parsimonious Encompassing diagnostic test.
nogum
Do not include the general model as a candidate for model selection.
noempty
Do not include the empty model as a candidate for model selection.
ic =arg
Set the information criterion used in model selection: “AIC” (Akaike information criteria, default), “BIC” (Schwarz information criteria), “HQ” (Hannan-Quin criteria).
blocks=int
Override the EViews’ determination of the number of blocks in which to split the estimation sample.
Lasso method options
General options
 
xtrans=arg (default=“none”)
Transformation of the regressor variables: “none” (none), “L1” (L1), “L2” (L2), “stdsmpl” (sample standard deviation), “stdpop” (population standard deviation), “minmax” (min-max).
lambdaratio=arg (default=0.0001)
Ratio of minimum to maximum lambda for EViews-supplied list.
nlambdas=arg (default=100)
Number of lambas for EViews-supplied list.
s
Use the current coefficient values in estimator coefficient vector as starting values (see also param).
s=number (default=1)
Specify a number between zero and one to determine starting values as a fraction of OLS values (out of range values are set to “s=1”).
maxit=integer
Maximum number of iterations.
conv=scalar
Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled estimates. The criterion will be set to the nearest value between 1e-24 and 0.2.
showopts / ‑showopts
[Do / do not] display the starting coefficient values and estimation options in the rotation output.
coef=arg
Specify the name of the coefficient vector (if specified by list); the default behavior is to use the “C” coefficient vector.
lambda=arg
Value of the penalty parameter. Can be a single number, list of space-delimited numbers, a workfile series object, or left blank for an EViews-supplied list (default). Values must be zero or greater.
w=arg
Weight series or expression.
wtype=arg (default=“istdev”)
Weight specification type: inverse standard deviation (“istdev”), inverse variance (“ivar”), standard deviation (“stdev”), variance (“var”).
wscale=arg
Weight scaling: EViews default (“eviews”), average (“avg”), none (“none”).
The default setting depends upon the weight type: “eviews” if “wtype=istdev”, “avg” for all others.
Cross Validation Options
 
cvmathod=arg (default=“kfold_cv”)
Cross-validation method: “kfold” (k-fold), “shuffle” (shuffle), “leavepout” (leave p out), “leave1out” (leave one out).
cvmeasure=arg (default=“mse”)
Error measurement from cross-validation: “mse” (mean-squared error), “mae” (mean absolute error), “r2” (r-squared).
training=arg
(default=0.8)
Proportion of data or number of data points in training set for shuffle method.
test=arg
(default=“mse”)
Proportion of data or number of data points in test set for shuffle method.
nreps=arg
(default=1)
Number of shuffle method repetitions.
nfolds=arg
(default=5)
Number of folds for k-fold method.
leaveout=arg
(default=2)
Number of data points left out for leave p out method.
Random Number Options
 
seed=positive_integer from 0 to 2,147,483,647
Seed the random number generator.
If not specified, EViews will seed random number generator with a single integer draw from the default global random number generator.
rnd=arg (default=“kn” or method previously set using rndseed
Type of random number generator: improved Knuth generator (“kn”), improved Mersenne Twister (“mt”), Knuth’s (1997) lagged Fibonacci generator used in EViews 4 (“kn4”) L’Ecuyer’s (1999) combined multiple recursive generator (“le”), Matsumoto and Nishimura’s (1998) Mersenne Twister used in EViews 4 (“mt4”).
Examples
eq1.varsel(method=comb,nvars=3) y c @ x1 x2 x3 x4 x5 x6 x7 x8
performs a combinatorial search routine to search for the three variables from the set of X1, X2, ..., X8, yielding the largest R-squared in a regression of Y on a constant and those three variables.
Cross-references
See “Regression Variable Selection”for extensive discussion.