msm

Switching mean specification (default is switching intercept).

exognv

Exogenous variables are non-regime specific (default is for exogenous variables to vary).

endogvary

Lagged endogenous variables are regime specific (default is for the endogenous variables to be non-varying).

noconst

Do not include a constant in exogenous regressors list.

fprobmat=arg

initprob=arg (default=“ergodic”)

Method for determining initial Markov regime probabilities: ergodic solution (“ergodic”), estimated parameter (“est”), equal probabilities (“uniform”), user-specified probabilities (“user”).

If “initprob=user” is specified, you will need to specify the “userinit=” option.

userinit=arg

Name of vector containing user-specified initial Markov probabilities. The vector should have rows equal to the number of states; we expand this to the size of the initial lag state vector where necessary for AR specifications.

For use in specifications containing both the “type=markov” and “initprob=user” options.

startnum=arg (default=0 or 25)

Number of random starting values tried. The default is 0 for user-supplied coefficients (option “s”) and 25 in all other cases.

startiter=arg (default=10)

Number of iterations taken after each random start before comparing objective to determine final starting value.

searchnum=arg (default=0)

Number of post-estimation perturbed starting values tried.

searchsds=arg (default=1)

Number of standard deviations to use in perturbed starts (if “searchnum=”) is specified.

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”).

optmethod = arg

Optimization method: “bfgs” (BFGS); “newton” (Newton-Raphson), “opg” or “bhhh” (OPG or BHHH), “legacy” (EViews legacy).

BFGS is the default method.

optstep = arg

 

Step method: “marquardt” (Marquardt); “dogleg” (Dogleg); “linesearch” (Line search).

Marquardt is the default method.

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.

cov=arg

Covariance method: “ordinary” (default method based on inverse of the estimated information matrix), “huber” or “white” (Huber-White sandwich method).

covinfo = arg

Information matrix method: “opg” (OPG); “hessian” (observed Hessian).

(Applicable when non-legacy “optmethod=”.)

nodf

Do not degree-of-freedom correct the coefficient covariance estimate.

coef=arg

Specify the name of the coefficient vector (if specified by list); the default behavior is to use the “C” coefficient vector.

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.

prompt

Force the dialog to appear from within a program.

p

Print results.