Summary and print methods for class 'dfm'. print.dfm just prints basic model information and the factor transition matrix \(\textbf{A}\), coef.dfm returns \(\textbf{A}\) and \(\textbf{C}\) in a plain list, whereas
summary.dfm returns all system matrices and additional residual and goodness of fit statistics—with a print method allowing full or compact printout.
Usage
# S3 method for class 'dfm'
print(x, digits = 4L, ...)
# S3 method for class 'dfm'
coef(object, ...)
# S3 method for class 'dfm'
logLik(object, ...)
# S3 method for class 'dfm'
summary(object, method = switch(object$em.method, none = "2s", "qml"), ...)
# S3 method for class 'dfm_summary'
print(x, digits = 4L, compact = sum(x$info["n"] > 15, x$info["n"] > 40), ...)Arguments
- x, object
an object class 'dfm'.
- digits
integer. The number of digits to print out.
- ...
not used.
- method
character. The factor estimates to use: one of
"qml","2s"or"pca".- compact
integer. Display a more compact printout:
0prints everything,1omits the observation matrix \(\textbf{C}\) and residual covariance matrixcov(resid(model)), and2omits all disaggregated information on the input data. Sensible default are chosen for different sizes of the input dataset so as to limit large printouts.
Value
Summary information following a dynamic factor model estimation. coef() returns \(\textbf{A}\) and \(\textbf{C}\).
Examples
mod <- DFM(diff(BM14_Q), 2, 3)
#> Converged after 26 iterations.
print(mod)
#> Dynamic Factor Model: n = 9, T = 117, r = 2, p = 3, %NA = 7.5973
#>
#> Factor Transition Matrix [A]
#> L1.f1 L1.f2 L2.f1 L2.f2 L3.f1 L3.f2
#> f1 0.6789 0.2413 -0.034 -0.4640 -0.0012 -0.1988
#> f2 0.0353 0.2270 -0.026 0.0645 -0.0744 0.1802
summary(mod)
#> Dynamic Factor Model: n = 9, T = 117, r = 2, p = 3, %NA = 7.5973
#>
#> Call: DFM(X = diff(BM14_Q), r = 2, p = 3)
#>
#> Summary Statistics of Factors [F]
#> N Mean Median SD Min Max
#> f1 117 -0.0084 0.3469 2.2931 -14.408 3.7167
#> f2 117 0.003 0.0867 0.8146 -2.4636 2.1071
#>
#> Factor Transition Matrix [A]
#> L1.f1 L1.f2 L2.f1 L2.f2 L3.f1 L3.f2
#> f1 0.67890 0.2413 -0.03401 -0.46403 -0.001235 -0.1988
#> f2 0.03533 0.2270 -0.02598 0.06451 -0.074449 0.1802
#>
#> Factor Covariance Matrix [cov(F)]
#> f1 f2
#> f1 5.2584 0.1622
#> f2 0.1622 0.6636
#>
#> Factor Transition Error Covariance Matrix [Q]
#> u1 u2
#> u1 2.7065 0.2039
#> u2 0.2039 0.6618
#>
#> Observation Matrix [C]
#> f1 f2
#> gdp 0.4094 -0.1237
#> priv_cons 0.2755 -0.4353
#> invest 0.3810 -0.3022
#> export 0.3842 0.4215
#> import 0.3911 0.2106
#> empl 0.3072 -0.3443
#> prductivity 0.2894 0.0222
#> capacity 0.2933 0.0157
#> gdp_us 0.2511 0.1259
#>
#> Observation Error Covariance Matrix [diag(R) - Restricted]
#> gdp priv_cons invest export import empl
#> 0.0953 0.4616 0.1685 0.0301 0.1232 0.4160
#> prductivity capacity gdp_us
#> 0.2317 0.4737 0.6360
#>
#> Observation Residual Covariance Matrix [cov(resid(DFM))]
#> gdp priv_cons invest export import empl
#> gdp 0.0670 -0.0046 -0.0096 -0.0038* -0.0357* -0.0679*
#> priv_cons -0.0046 0.4173 -0.0735* 0.0059 0.0060 -0.0777*
#> invest -0.0096 -0.0735* 0.1263 -0.0010 -0.0210 -0.0620*
#> export -0.0038* 0.0059 -0.0010 0.0061 -0.0119* 0.0058
#> import -0.0357* 0.0060 -0.0210 -0.0119* 0.1090 0.0367
#> empl -0.0679* -0.0777* -0.0620* 0.0058 0.0367 0.3816
#> prductivity 0.0683* 0.0273 0.0173 -0.0024 -0.0748* -0.2119*
#> capacity -0.0470* -0.0978* -0.0320 -0.0201* 0.0624* 0.0628
#> gdp_us -0.0209 -0.0023 0.0045 -0.0095 -0.0252 -0.0236
#> prductivity capacity gdp_us
#> gdp 0.0683* -0.0470* -0.0209
#> priv_cons 0.0273 -0.0978* -0.0023
#> invest 0.0173 -0.0320 0.0045
#> export -0.0024 -0.0201* -0.0095
#> import -0.0748* 0.0624* -0.0252
#> empl -0.2119* 0.0628 -0.0236
#> prductivity 0.2215 -0.1119* -0.0496
#> capacity -0.1119* 0.4666 -0.0059
#> gdp_us -0.0496 -0.0059 0.6353
#>
#> Residual AR(1) Serial Correlation
#> gdp priv_cons invest export import empl
#> -0.149924 -0.272110 -0.206251 -0.215038 -0.007949 0.434361
#> prductivity capacity gdp_us
#> 0.053696 0.091852 0.179658
#>
#> Summary of Residual AR(1) Serial Correlations
#> N Mean Median SD Min Max
#> 9 -0.0102 -0.0079 0.2282 -0.2721 0.4344
#>
#> Goodness of Fit: R-Squared
#> gdp priv_cons invest export import empl
#> 0.9330 0.5827 0.8737 0.9939 0.8910 0.6184
#> prductivity capacity gdp_us
#> 0.7785 0.5334 0.3647
#>
#> Summary of Individual R-Squared's
#> N Mean Median SD Min Max
#> 9 0.7299 0.7785 0.2139 0.3647 0.9939