Simplify print output for SARIMA/RegARIMA

[AQLT]

I propose to simplify the print output of the SARIMA/RegARIMA and seasonal adjustment models. A message with a reference to the summary() method is added (which can be disabled with the summary_info option):

library(rjd3toolkit)
library(rjd3x13)
y <- rjd3toolkit::ABS$X0.2.09.10.M
sa_e <- sarima_estimate(y, order = c(0,1,1), seasonal = c(0,1,1))
reg <- regarima(y)
sa_e
#> SARIMA model: (0,1,1) (0,1,1) [12]
#> 
#> Coefficients
#>  theta(1) btheta(1) 
#>   -0.8764   -0.3875 
#> 
#> No regression variables
#> 
#> For a more detailed output, use the 'summary()' function.
summary(sa_e) # not changed
#> SARIMA model: (0,1,1) (0,1,1) [12]
#> 
#> Coefficients
#>           Estimate Std. Error  T-stat Pr(>|t|)    
#> theta(1)  -0.87640    0.02290 -38.274  < 2e-16 ***
#> btheta(1) -0.38754    0.05071  -7.642 1.54e-13 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> No regression variables
#> Number of observations: 425, Number of effective observations: 412, Number of parameters: 3
#> Loglikelihood: -2218.964
#> Standard error of the regression (ML estimate): 52.59137 
#> AIC: 4443.928, AICc: 4443.987, BIC: 4455.991
reg
#> Log-transformation: yes 
#> SARIMA model: (2,1,1) (0,1,1)
#> 
#> SARIMA coefficients:
#>    phi(1)    phi(2)  theta(1) btheta(1) 
#>    0.3474    0.2173   -0.6994   -0.4804 
#> 
#> Regression model:
#>              td          easter TC (2000-06-01) AO (2000-07-01) 
#>        0.002323        0.052011        0.159034       -0.290077 
#> 
#> For a more detailed output, use the 'summary()' function.
summary(reg) # not changed
#> Log-transformation: yes 
#> SARIMA model: (2,1,1) (0,1,1)
#> 
#> Coefficients
#>           Estimate Std. Error  T-stat Pr(>|t|)    
#> phi(1)     0.34740    0.06502   5.343 1.53e-07 ***
#> phi(2)     0.21733    0.06000   3.622 0.000329 ***
#> theta(1)  -0.69937    0.05115 -13.672  < 2e-16 ***
#> btheta(1) -0.48038    0.06993  -6.869 2.45e-11 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Regression model:
#>                   Estimate Std. Error T-stat Pr(>|t|)    
#> td               0.0023233  0.0006844  3.395 0.000755 ***
#> easter           0.0520113  0.0084894  6.127 2.14e-09 ***
#> TC (2000-06-01)  0.1590340  0.0288578  5.511 6.38e-08 ***
#> AO (2000-07-01) -0.2900774  0.0400551 -7.242 2.26e-12 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> Number of observations: 425, Number of effective observations: 412, Number of parameters: 9
#> Loglikelihood: 746.7517, Adjusted loglikelihood: -2120.875
#> Standard error of the regression (ML estimate): 0.03927991 
#> AIC: 4259.75, AICc: 4260.198, BIC: 4295.939