(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
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
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
Mdlcontains them)Variance
Degrees of freedom for the t distribution
Data Types: double
Version History
Introduced in R2013bprint will be removed in a future release. Use summarize
instead.
This list shows the differences between print and
summarize:
For an unestimated (custom)
regARIMAmodel input,summarizereturns the standard object display of the model.For an estimated
regARIMAmodel input, as returned byestimate,summarizeprints an estimation summary in a MATLAB table and lists other estimation statistics.summarizereturns the estimation statistics in an output structure array.
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