Model: ARIMA(0,2,3)(0,0,2)[12]
Coefficients:
Moving Average 1
Estimate: -0.4367
Standard Error: 0.0334
Moving Average 2
Estimate: -0.3916
Standard Error: 0.0331
Moving Average 3
Estimate: -0.0549
Standard Error: 0.0352
Seasonal Moving Average 1
Estimate: -0.1210
Standard Error: 0.0334
Seasonal Moving Average 2
Estimate: -0.0651
Standard Error: 0.0320
Residual Variance: 0.1352
Model Fit Metrics:
BIC: 826.06
AICc: 797.06
Forecast Values (Index 1982-1984 = 100):
2025
Sep: 324
Oct: 325
Nov: 326
Dec: 327
2026
Jan: 328
Feb: 329
Mar: 329
Apr: 330
May: 331
Jun: 332
Jul: 333
Aug: 334
Sep: 335
Oct: 335
Nov: 336
Dec: 337
2027
Jan: 338
Feb: 339
Mar: 340
Apr: 340
May: 341
Jun: 342
Jul: 343
Aug: 344
Sep: 345
Oct: 346
Nov: 346
Dec: 347
Model: ETS(M,Ad,N)
Coefficients:
Alpha (level): 0.9999
Beta (trend): 0.2839957
Phi (damping parameter): 0.979999
Level (l₀): 21.31322
Trend (b₀): 0.1721149
Residual Variance: 0
Model Fit Metrics:
BIC: 3837.218
AICc: 3808.207
Forecast Values (Index 1982-1984 = 100):
2025
Sep: 324
Oct: 325
Nov: 326
Dec: 326
2026
Jan: 327
Feb: 328
Mar: 328
Apr: 329
May: 330
Jun: 330
Jul: 331
Aug: 332
Sep: 332
Oct: 333
Nov: 333
Dec: 334
2027
Jan: 334
Feb: 335
Mar: 335
Apr: 336
May: 337
Jun: 337
Jul: 337
Aug: 338
Sep: 338
Oct: 339
Nov: 339
Dec: 340E