midwgt=arg

MIDAS weight method: step function(“step”), normalized exponential Almon (“expalmon”), normalized beta function (“beta”), U-MIDAS (“umidas”), Auto-search/GETS (“autogets”) or the default Almon/PDL weighting

(“almon”).

lag=arg

Method for specifying the number of lags of the high frequency regressor to use: lag selection (“auto”), fixed (“fixed”). The default is “lag=fixed”.

maxlag=arg

Maximum number of lags of the high frequency regressor to use when using lag selection. For use when “lag=auto”. The default value is 4.

fixedlag=arg

Fixed number of lags of the high frequency regressor to use. For use when “lags=fixed”. The default value is 4.

steps=integer

Stepsize (number of high frequency periods to group). For use when “midwgt=step”.

polynomial=integer

Polynomial degree. For use when Almon/PDL weighting is employed.

beta=arg

Beta function restriction: none (“none”), trend coefficient equals 1 (“trend”), endpoints coefficient equals 0 (“endpoint”), both trend and endpoints restriction (“both”).

For use when “midwgt=beta”. The default is “beta=none”.

optmethod = arg

Optimization method for nonlinear estimation: “bfgs” (BFGS); “newton” (Newton-Raphson), “opg” or “bhhh” (OPG or BHHH), “hybrid” (initial BHHH followed by BFGS).

Hybrid is the default method.

optstep = arg

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

Marquardt is the default method.

cov=arg

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

covinfo = arg

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

freq = key

Set the frequency conversion method. Key can be “first” (the higher frequency data are used from the first observation in the lower frequency period), “last” (default, the higher frequency data are used from the last observation in the lower frequency), or “match” (a specific date matching series from each page is used).

freqsrc = arg

Set the source date matching series. Only applies if freq=match is used.

freqdest = arg

Set the destination date matching series. Only applies if freq=match is used.

nodf

Do not perform degree of freedom corrections in computing coefficient covariance matrix. The default is to use degree of freedom corrections.

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 estimator coefficient vector as starting values in nonlinear estimation (see also param ).

s=number

Determine starting values for nonlinear estimation.. Specify a number between zero and one representing the fraction of preliminary EViews chosen values. Note that out of range values are set to “s=1”. Specifying “s=0” initializes coefficients to zero. By default EViews uses “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 estimation results.

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.