Refresh a Workspace or SA-Processing

Usage

jsap_refresh(
  jsap,
  policy = c("FreeParameters", "Complete", "Outliers_StochasticComponent", "Outliers",
    "FixedParameters", "FixedAutoRegressiveParameters", "Fixed"),
  period = 0,
  start = NULL,
  end = NULL,
  info = c("All", "Data", "None")
)

jws_refresh(
  jws,
  policy = c("FreeParameters", "Complete", "Outliers_StochasticComponent", "Outliers",
    "FixedParameters", "FixedAutoRegressiveParameters", "Fixed"),
  period = 0,
  start = NULL,
  end = NULL,
  info = c("All", "Data", "None")
)

Arguments

policy: refresh policy to apply (see details).
period, start, end: additional parameters used to specify the span When policy = "Outliers" or policy = "Outliers_StochasticComponent" period: numeric, number of observations in a year (12, 4...), compulsory, if mis-specified or missing, re-estimation with refreshed specification won't work. end has to be specified as the date from which outliers will be re-identified
info: indication on how data should be refreshed All: data and metadata will be refreshed (default) Data: data will be refreshed, not metadata None: nor data neither metadata will be refreshed, to be used for updating specifications only.
jws, jsap: Java Workspace or SA-Processing

Value

refreshed workspace or SAP

Details

A particular selection of parameters to be kept fixed or re-estimated is called a revision policy. Workspace has to be computed before refresh When refreshing data, empty your cache by restarting your R session, before refreshing, otherwise the specification will be refreshed but the new data will not be taken into account.

Available refresh policies are:

Fixed: applying the current pre-adjustment reg-arima model and replacing forecasts by new raw data points; X11 (or SEATS) and Benchmarking part parameters are untouched.
FixedParameters: pre-adjustment reg-arima model is partially modified: regression coefficients will be re-estimated but regression variables, Arima orders and coefficients are unchanged; X11 (or SEATS) and Benchmarking part parameters are untouched.
FixedAutoRegressiveParameters: same as FixedParameters but Arima Moving Average coefficients (MA) are also re-estimated, Auto-regressive (AR) coefficients are kept fixed; X11 (or SEATS) and Benchmarking part parameters are untouched.
FreeParameters: all regression and Arima model coefficients are re-estimated, regression variables and Arima orders are kept fixed; X11 (or SEATS) and Benchmarking part parameters are untouched.
Outliers: regression variables and Arima orders are kept fixed, but outliers will be re-detected on the defined span, thus all regression and Arima model coefficients are re-estimated; X11 (or SEATS) and Benchmarking part parameters are untouched.
Outliers_StochasticComponent: same as "Outliers" but Arima model orders (p,d,q)(P,D,Q) can also be re-identified; X11 (or SEATS) and Benchmarking part parameters are untouched.
Complete: All the parameters are re-identified and re-estimated, unless constrained in the reference spec. X11 (or SEATS) and Benchmarking part parameters are entirely reset to values in the reference specification.

References

More information on revision policies in JDemetra+ documentation: https://doc.jdemetra.org/a-rev-policies

Examples


# Load workspace
file <- system.file("workspaces", "workspace_test_refresh.xml", package = "rjd3workspace")
# \donttest{
jws <- jws_open(file)
jws_compute(jws)
# Read current workspace: reference spec and estimation spec
rws <- read_workspace(jws, compute= TRUE)
rws$processing$`SAProcessing-1`$`RF0811`$referenceSpec
#> Specification
#> 
#> Series
#> Serie span: All 
#> Preliminary Check: Yes
#> 
#> Estimate
#> Model span: All 
#> 
#> Tolerance: 1e-07
#> 
#> Transformation
#> Function: AUTO
#> AIC difference: -2
#> Adjust: NONE
#> 
#> Regression
#> No calendar regressor
#> 
#> Easter: No
#> 
#> Pre-specified outliers: 1
#> 	- LS.2024-01, coefficient: 0 (UNDEFINED)
#> Ramps: No
#> 
#> Outliers
#> Detection span: All 
#> Outliers type: 
#> 	- AO, critical value : 0 (Auto)
#> 	- LS, critical value : 0 (Auto)
#> 	- TC, critical value : 0 (Auto)
#> TC rate: 0.7 (Auto)
#> Method: ADDONE (Auto)
#> 
#> ARIMA
#> SARIMA model: (0,1,1) (0,1,1)
#> 
#> SARIMA coefficients:
#>  theta(1) btheta(1) 
#>         0         0 
#> 
#> Specification X11
#> Seasonal component: Yes
#> Length of the Henderson filter: 0
#> Seasonal filter: FILTER_MSR
#> Boundaries used for extreme values correction : 
#> 	 lower_sigma:  1.5 
#> 	 upper_sigma:  2.5
#> Nb of forecasts: -1
#> Nb of backcasts: 0
#> Calendar sigma: NONE
#> 
#> Benchmarking
#> Is enabled: No
rws$processing$`SAProcessing-1`$`RF0811`$estimationSpec
#> Specification
#> 
#> Series
#> Serie span: From 2012-01-01 
#> Preliminary Check: Yes
#> 
#> Estimate
#> Model span: From 2015-01-01 
#> 
#> Tolerance: 1e-07
#> 
#> Transformation
#> Function: LEVEL
#> AIC difference: -2
#> Adjust: NONE
#> 
#> Regression
#> No calendar regressor
#> 
#> Easter: JULIAN 
#> Duration: 8 (Auto) 
#> Test: NO  
#> Coef:
#> 	- Type: UNDEFINED  
#> 	- Value: 0 
#> 
#> Pre-specified outliers: 4
#> 	- AO.2020-03, coefficient: 0 (UNDEFINED)
#> 	- AO.2020-04, coefficient: 0 (UNDEFINED)
#> 	- AO.2020-05, coefficient: 0 (UNDEFINED)
#> 	- AO.2024-04, coefficient: 0 (UNDEFINED)
#> Ramps: No
#> 
#> Outliers
#> Detection span: All 
#> Outliers type: 
#> 	- AO, critical value : 0 (Auto)
#> 	- LS, critical value : 0 (Auto)
#> TC rate: 0.7 (Auto)
#> Method: ADDONE (Auto)
#> 
#> ARIMA
#> SARIMA model: (1,1,1) (1,1,1)
#> 
#> SARIMA coefficients:
#>    phi(1)  theta(1)   bphi(1) btheta(1) 
#>         0         0         0         0 
#> 
#> Specification X11
#> Seasonal component: Yes
#> Length of the Henderson filter: 0
#> Seasonal filter: FILTER_MSR
#> Boundaries used for extreme values correction : 
#> 	 lower_sigma:  1.5 
#> 	 upper_sigma:  2.5
#> Nb of forecasts: -2
#> Nb of backcasts: 0
#> Calendar sigma: NONE
#> 
#> Benchmarking
#> Enabled: Yes
#> Target: TARGET_CALENDARADJUSTED (Auto)
#> Lambda: 1 (Auto)
#> Rho: 1 (Auto)
#> Bias: BIAS_NONE (Auto)
#> Use forecast: Yes
# Refresh workspace COMPLETE
jws_refresh(jws, policy = "Complete")
# Read refreshed workspace: new estimation spec
rws2 <- read_workspace(jws, compute= TRUE)
rws2$processing$`SAProcessing-1`$`RF0811`$estimationSpec
#> Specification
#> 
#> Series
#> Serie span: All 
#> Preliminary Check: Yes
#> 
#> Estimate
#> Model span: All 
#> 
#> Tolerance: 1e-07
#> 
#> Transformation
#> Function: AUTO
#> AIC difference: -2
#> Adjust: NONE
#> 
#> Regression
#> No calendar regressor
#> 
#> Easter: No
#> 
#> Pre-specified outliers: 1
#> 	- LS.2024-01, coefficient: 0 (UNDEFINED)
#> Ramps: No
#> 
#> Outliers
#> Detection span: All 
#> Outliers type: 
#> 	- AO, critical value : 0 (Auto)
#> 	- LS, critical value : 0 (Auto)
#> 	- TC, critical value : 0 (Auto)
#> TC rate: 0.7 (Auto)
#> Method: ADDONE (Auto)
#> 
#> ARIMA
#> SARIMA model: (0,1,1) (0,1,1)
#> 
#> SARIMA coefficients:
#>  theta(1) btheta(1) 
#>         0         0 
#> 
#> Specification X11
#> Seasonal component: Yes
#> Length of the Henderson filter: 0
#> Seasonal filter: FILTER_MSR
#> Boundaries used for extreme values correction : 
#> 	 lower_sigma:  1.5 
#> 	 upper_sigma:  2.5
#> Nb of forecasts: -1
#> Nb of backcasts: 0
#> Calendar sigma: NONE
#> 
#> Benchmarking
#> Is enabled: No
# Refresh workspace Outliers (like "lastoutliers in the GUI, but with custom start date)
jws <- jws_open(file)
jws_compute(jws)
jws_refresh(jws, policy = "Outliers", period=12, end=c(2020,4))
# Read refreshed workspace: new estimation spec
rws3 <- read_workspace(jws, compute= TRUE)
rws3$processing$`SAProcessing-1`$`RF0811`$estimationSpec
#> Specification
#> 
#> Series
#> Serie span: From 2012-01-01 
#> Preliminary Check: Yes
#> 
#> Estimate
#> Model span: From 2015-01-01 
#> 
#> Tolerance: 1e-07
#> 
#> Transformation
#> Function: LEVEL
#> AIC difference: -2
#> Adjust: NONE
#> 
#> Regression
#> No calendar regressor
#> 
#> Easter: STANDARD 
#> Duration: 8 (Auto) 
#> Test: NO  
#> Coef:
#> 	- Type: ESTIMATED  
#> 	- Value: -18.74348 
#> 
#> Pre-specified outliers: 2
#> 	- LS.2024-01, coefficient: 0 (INITIAL)
#> 	- AO.2020-03, coefficient: -23.2364877397156 (INITIAL)
#> Ramps: No
#> 
#> Outliers
#> Detection span: From 2020-04-01 
#> Outliers type: 
#> 	- AO, critical value : 0 (Auto)
#> 	- LS, critical value : 0 (Auto)
#> 	- TC, critical value : 0 (Auto)
#> TC rate: 0.7 (Auto)
#> Method: ADDONE (Auto)
#> 
#> ARIMA
#> SARIMA model: (1,1,1) (1,1,1)
#> 
#> SARIMA coefficients:
#>    phi(1)  theta(1)   bphi(1) btheta(1) 
#>         0         0         0         0 
#> 
#> Specification X11
#> Seasonal component: Yes
#> Length of the Henderson filter: 0
#> Seasonal filter: FILTER_MSR
#> Boundaries used for extreme values correction : 
#> 	 lower_sigma:  1.5 
#> 	 upper_sigma:  2.5
#> Nb of forecasts: -2
#> Nb of backcasts: 0
#> Calendar sigma: NONE
#> 
#> Benchmarking
#> Enabled: Yes
#> Target: TARGET_CALENDARADJUSTED (Auto)
#> Lambda: 1 (Auto)
#> Rho: 1 (Auto)
#> Bias: BIAS_NONE (Auto)
#> Use forecast: Yes
# }