AirPassengersX12Batch.Rdx12Batch object of four AirPassengers series with paramters and output objects
data(AirPassengersX12Batch)data(AirPassengersX12Batch)
summary(AirPassengersX12Batch)
#> -----------------------------------------------------------------------------------
#> -------------------------- Series_1 ------------------------------------
#> -----------------------------------------------------------------------------------
#>
#> Time Series
#>
#> Frequency: 12
#> Span: 1st month,1949 to 12th month,1960
#>
#> Model Definition
#>
#> ARIMA Model: (1,1,0)(0,1,1)
#> Model Span: 1st month,1949 to 12th month,1960
#> Transformation: Automatic selection : Log(y)
#> Regression Model: none
#>
#> Outlier Detection
#>
#> Outlier Span: 1st month,1949 to 12th month,1960
#> Critical |t| for outliers:
#> aocrit1 aocrit2 lscrit1 lscrit2 tccrit1 tccrit2
#> "3.89" "*" "3.89" "*" "3.89" "*"
#> Total Number of Outliers: 0
#> Automatically Identified Outliers: 0
#>
#> 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
#> Seasonal moving average used for the final iteration:
#> 3x3 (Based on the size of the global moving seasonality ratio (msr))
#> 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: 1st month,1949 to 12th month,1960
#> Transformation: Automatic selection : Log(y)
#> Regression Model: Automatically Identified Outliers
#>
#> Outlier Detection
#>
#> Outlier Span: 1st month,1949 to 12th month,1960
#> Critical |t| for outliers:
#> aocrit1 aocrit2 lscrit tccrit
#> "3.89" "*" "3.5" "2.5"
#> Total Number of Outliers: 6
#> Automatically Identified Outliers: 6
#>
#> Regression Model
#> variable coef stderr tval
#> 1 autooutlier_TC1951.May 0.078 0.023 3.321
#> 2 autooutlier_TC1951.Jun -0.099 0.024 -4.174
#> 3 autooutlier_TC1952.Mar -0.083 0.023 -3.610
#> 4 autooutlier_LS1953.Jun -0.090 0.023 -3.851
#> 5 autooutlier_TC1954.Feb -0.075 0.023 -3.243
#> 6 autooutlier_AO1960.Mar -0.104 0.024 -4.270
#>
#> Seasonal Adjustment
#>
#> Identifiable Seasonality: yes
#> Seasonal Peaks: rsd
#> Trading Day Peaks: rsd
#> Overall Index of Quality of SA
#> (Acceptance Region from 0 to 1)
#> Q: 0.2
#> Number of M statistics outside the limits: 0
#>
#> SA decomposition: multiplicative
#> Seasonal moving average used for the final iteration:
#> 3x3 (Based on the size of the global moving seasonality ratio (msr))
#> 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: 1st month,1949 to 12th month,1960
#> Transformation: Automatic selection : Log(y)
#> Regression Model: none
#>
#> Outlier Detection
#>
#> Outlier Span: 1st month,1949 to 12th month,1960
#> Critical |t| for outliers:
#> aocrit1 aocrit2 lscrit1 lscrit2 tccrit1 tccrit2
#> "3.89" "*" "3.89" "*" "3.89" "*"
#> Total Number of Outliers: 0
#> Automatically Identified Outliers: 0
#>
#> 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
#> Seasonal moving average used for the final iteration:
#> 3x3 (Based on the size of the global moving seasonality ratio (msr))
#> 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: (0 1 1)(0 1 1) (Automatic Model Choice)
#> Model Span: 1st month,1949 to 12th month,1960
#> Transformation: Automatic selection : Log(y)
#> Regression Model: none
#>
#> Outlier Detection
#>
#> Outlier Span: 1st month,1949 to 12th month,1960
#> Critical |t| for outliers:
#> aocrit lscrit tccrit
#> 3.5 3.5 3.5
#> Total Number of Outliers: 0
#> Automatically Identified Outliers: 0
#>
#> 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
#> Seasonal moving average used for the final iteration:
#> 3x3 (Based on the size of the global moving seasonality ratio (msr))
#> Moving average used to estimate the final trend-cycle: 9-term Henderson filter