(To be removed) Display estimation results for regression models with ARIMA errors
Description
print(
displays parameter estimates, standard errors, and t statistics of a
fitted regression model with ARIMA model.EstMdl
,EstParamCov
)
Examples
Print Estimation Results of Regression Model with ARIMA Errors
Regress GDP onto CPI using a regression model with ARMA(1,1) errors, and print the results.
Load the US Macroeconomic data set and preprocess the data.
load Data_USEconModel
logGDP = log(DataTable.GDP);
dlogGDP = diff(logGDP);
dCPI = diff(DataTable.CPIAUCSL);
Fit the model to the data.
Mdl = regARIMA(1,0,1);
[EstMdl,EstParamCov] = estimate(Mdl,dlogGDP,X=dCPI,Display="off");
Print the estimates.
print(EstMdl,EstParamCov)
Warning: PRINT will be removed in a future release; use SUMMARIZE instead.
Regression with ARIMA(1,0,1) Error Model: ------------------------------------------ Conditional Probability Distribution: Gaussian Standard t Parameter Value Error Statistic ----------- ----------- ------------ ----------- Intercept 0.014776 0.00146271 10.1018 AR{1} 0.605274 0.0892902 6.77872 MA{1} -0.161651 0.10956 -1.47546 Beta1 0.00204403 0.000706163 2.89456 Variance 9.35782e-05 6.03135e-06 15.5153
Input Arguments
EstParamCov
— Estimation error variance-covariance
square numeric matrix
Estimation error variance-covariance, specified as a square numeric matrix.
EstParamCov
is a square matrix with a row and column for each
parameter known to the optimizer that estimate
uses to fit
EstMdl
. Known parameters include all parameters
estimate
estimates. If you specify equality constraints on a
parameter for estimation, the parameter is known and the rows and columns associated
with it contain zeros.
print
omits coefficients of lag operator polynomials at
lags excluded from EstMdl
.
print
arranges the parameters in
ParamCov
as follows:
Intercept
Nonzero AR coefficients at positive lags
Nonzero SAR coefficients at positive lags
Nonzero MA coefficients at positive lags
Nonzero SMA coefficients at positive lags
Regression coefficients (when
Mdl
contains them)Variance
Degrees of freedom for the t distribution
Data Types: double
Version History
Introduced in R2013bR2018a: Warns
print
will be removed in a future release. Use summarize
instead.
This list shows the differences between print
and
summarize
:
For an unestimated (custom)
regARIMA
model input,summarize
returns the standard object display of the model.For an estimated
regARIMA
model input, as returned byestimate
,summarize
prints an estimation summary in a MATLAB table and lists other estimation statistics.summarize
returns the estimation statistics in an output structure array.
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