R Under development (unstable) (2025-11-16 r89026 ucrt) -- "Unsuffered Consequences" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > if ( requireNamespace("tinytest", quietly=TRUE) ){ + options(x12.delete = TRUE) + tinytest::test_package("x12") + } Loading required package: x13binary x12 is ready to use. Use the package x12GUI for a Graphical User Interface. By default the X13-ARIMA-SEATS binaries provided by the R package x13binary are used but this can be changed with x12path(validpath) --------------- Suggestions and bug-reports can be submitted at: https://github.com/statistikat/x12/issues test_AirPassengers.R.......... 0 tests test_AirPassengers.R.......... 0 tests X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Rout.spc Storing any program output into Rout.html Storing any program error messages into Rout_err.html Storing any diagnostics output into gra_Rout/Rout.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Rout.spc at 111 0, 0 00.00.00 test_AirPassengers.R.......... 0 tests Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0 1 1)(0 1 1) (Automatic Model Choice) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter test_AirPassengers.R.......... 0 tests test_AirPassengers.R.......... 1 tests OK test_AirPassengers.R.......... 2 tests OK X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Rout.spc Storing any program output into Rout.html Storing any program error messages into Rout_err.html Storing any diagnostics output into gra_Rout/Rout.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Rout.spc at 111 0, 0 00.00.00 test_AirPassengers.R.......... 2 tests OK -------------------------- Rout ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0 1 1)(0 1 1) (Automatic Model Choice) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter test_AirPassengers.R.......... 2 tests OK test_AirPassengers.R.......... 3 tests OK test_AirPassengers.R.......... 4 tests OK X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_1.spc Storing any program output into Series_1.html Storing any program error messages into Series_1_err.html Storing any diagnostics output into gra_Series_1/Series_1.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_1.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_2.spc Storing any program output into Series_2.html Storing any program error messages into Series_2_err.html Storing any diagnostics output into gra_Series_2/Series_2.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_2.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_3.spc Storing any program output into Series_3.html Storing any program error messages into Series_3_err.html Storing any diagnostics output into gra_Series_3/Series_3.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_3.spc at 111 0, 0 00.00.00 Time difference of 4.748129 secs test_AirPassengers.R.......... 4 tests OK ----------------------------------------------------------------------------------- -------------------------- Series_1 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0 1 1)(0 1 1) (Automatic Model Choice) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter ----------------------------------------------------------------------------------- -------------------------- Series_2 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0 1 1)(0 1 1) (Automatic Model Choice) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter ----------------------------------------------------------------------------------- -------------------------- Series_3 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0 1 1)(0 1 1) (Automatic Model Choice) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter test_AirPassengers.R.......... 4 tests OK test_AirPassengers.R.......... 5 tests OK test_AirPassengers.R.......... 6 tests OK test_AirPassengers.R.......... 7 tests OK test_AirPassengers.R.......... 7 tests OK The parameters for all objects are changed. test_AirPassengers.R.......... 7 tests OK test_AirPassengers.R.......... 7 tests OK test_AirPassengers.R.......... 7 tests OK test_AirPassengers.R.......... 7 tests OK test_AirPassengers.R.......... 7 tests OK X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_1.spc Storing any program output into Series_1.html Storing any program error messages into Series_1_err.html Storing any diagnostics output into gra_Series_1/Series_1.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_1.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_2.spc Storing any program output into Series_2.html Storing any program error messages into Series_2_err.html Storing any diagnostics output into gra_Series_2/Series_2.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_2.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_3.spc Storing any program output into Series_3.html Storing any program error messages into Series_3_err.html Storing any diagnostics output into gra_Series_3/Series_3.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_3.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_4.spc Storing any program output into Series_4.html Storing any program error messages into Series_4_err.html Storing any diagnostics output into gra_Series_4/Series_4.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_4.spc at 111 0, 0 00.00.00 Time difference of 0.9761069 secs test_AirPassengers.R.......... 7 tests OK ----------------------------------------------------------------------------------- -------------------------- Series_1 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (1,1,0)(1,1,0) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: none Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter ----------------------------------------------------------------------------------- -------------------------- Series_2 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0,1,1)(0,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter ----------------------------------------------------------------------------------- -------------------------- Series_3 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0,1,1)(1,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: none Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter ----------------------------------------------------------------------------------- -------------------------- Series_4 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (1,1,1)(1,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter test_AirPassengers.R.......... 7 tests OK test_AirPassengers.R.......... 8 tests OK test_AirPassengers.R.......... 9 tests OK test_AirPassengers.R.......... 10 tests OK test_AirPassengers.R.......... 10 tests OK Warning: 'automdl' is ignored because an ARIMA model has been specified! X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_1.spc Storing any program output into Series_1.html Storing any program error messages into Series_1_err.html Storing any diagnostics output into gra_Series_1/Series_1.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_1.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_2.spc Storing any program output into Series_2.html Storing any program error messages into Series_2_err.html Storing any diagnostics output into gra_Series_2/Series_2.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_2.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_3.spc Storing any program output into Series_3.html Storing any program error messages into Series_3_err.html Storing any diagnostics output into gra_Series_3/Series_3.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_3.spc at 111 0, 0 00.00.00 X-13ARIMA-SEATS Seasonal Adjustment Program Version Number 1.1 Build 60 Execution began 111 0, 0 00.00.00 Reading input spec file from Series_4.spc Storing any program output into Series_4.html Storing any program error messages into Series_4_err.html Storing any diagnostics output into gra_Series_4/Series_4.udg NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) has been stored in the directory specified by the graphics (-g) option. NOTE: The X-13ARIMA-SEATS diagnostic file (.udg) is generated since the graphics (-g) option was specified. WARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the regARIMA residuals. WARNING: At least one visually significant trading day peak has been found in one or more of the estimated spectra. Execution complete for Series_4.spc at 111 0, 0 00.00.00 Time difference of 0.9916282 secs test_AirPassengers.R.......... 10 tests OK ----------------------------------------------------------------------------------- -------------------------- Series_1 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (1,1,0)(1,1,0) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: none Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- ----------------------------------------------------------------------------------- -------------------------- Series_2 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0,1,1)(0,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- ----------------------------------------------------------------------------------- -------------------------- Series_3 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0,1,1)(1,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: none Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- ----------------------------------------------------------------------------------- -------------------------- Series_4 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (1,1,1)(1,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- test_AirPassengers.R.......... 10 tests OK test_AirPassengers.R.......... 10 tests OK ----------------------------------------------------------------------------------- -------------------------- Series_1 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (1,1,0)(1,1,0) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: none Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter ----------------------------------------------------------------------------------- -------------------------- Series_2 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0,1,1)(0,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- ----------------------------------------------------------------------------------- -------------------------- Series_3 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (0,1,1)(1,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: none Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- ----------------------------------------------------------------------------------- -------------------------- Series_4 ------------------------------------ ----------------------------------------------------------------------------------- Time Series Frequency: 12 Span: 1st month,1949 to 12th month,1960 Model Definition ARIMA Model: (1,1,1)(1,1,1) Model Span: Transformation: Automatic selection : Log(y) Regression Model: none Outlier Detection No outlier detection performed Seasonal Adjustment Identifiable Seasonality: yes Seasonal Peaks: rsd Trading Day Peaks: sa irr Overall Index of Quality of SA (Acceptance Region from 0 to 1) Q: 0.26 Number of M statistics outside the limits: 0 SA decomposition: multiplicative Moving average used to estimate the seasonal factors: 3x3 Moving average used to estimate the final trend-cycle: 9-term Henderson filter --- No valid previous runs. --- test_AirPassengers.R.......... 10 tests OK 10.1s All ok, 10 results (10.1s) > > proc.time() user system elapsed 1.25 0.26 10.62