Monte Carlo AR(1) data with alpha = 0



Monte Carlo AR(1) data with alpha = 0.7

X=Time Y=AR(1) Series

The ARIMA Procedure Yt = 0.7Yt-1 + ut

Name of Variable = x2

Mean of Working Series -0.22223

Standard Deviation 1.589171

Number of Observations 200

Autocorrelations

Lag Covariance Correlation -1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1

0 2.525463 1.00000 | |********************|

1 2.000747 0.79223 | . |**************** |

2 1.481214 0.58651 | . |************ |

3 1.061147 0.42018 | . |******** |

4 0.764765 0.30282 | . |****** |

5 0.423600 0.16773 | . |*** . |

6 0.290481 0.11502 | . |** . |

7 0.322476 0.12769 | . |*** . |

8 0.272510 0.10790 | . |** . |

9 0.195309 0.07734 | . |** . |

10 0.126098 0.04993 | . |* . |

11 0.00045990 0.00018 | . | . |

12 -0.217297 -.08604 | . **| . |

13 -0.337171 -.13351 | . ***| . |

14 -0.279029 -.11049 | . **| . |

15 -0.129674 -.05135 | . *| . |

16 0.121938 0.04828 | . |* . |

17 0.236404 0.09361 | . |** . |

18 0.301865 0.11953 | . |** . |

19 0.233485 0.09245 | . |** . |

20 0.131253 0.05197 | . |* . |

Partial Autocorrelations

Lag Correlation -1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1

1 0.79223 | . |**************** |

2 -0.11042 | .**| . |

3 -0.02257 | . | . |

4 0.01423 | . | . |

5 -0.13932 | ***| . |

6 0.12842 | . |*** |

7 0.11150 | . |**. |

8 -0.10317 | .**| . |

9 0.00377 | . | . |

10 -0.02879 | . *| . |

11 -0.10391 | .**| . |

12 -0.08483 | .**| . |

13 0.02341 | . | . |

14 0.09250 | . |**. |

15 0.09371 | . |**. |

16 0.15957 | . |*** |

17 -0.11878 | .**| . |

18 -0.00073 | . | . |

19 -0.05243 | . *| . |

20 -0.04240 | . *| . |

Autocorrelation Check for White Noise

To Chi- Pr >

Lag Square DF ChiSq ---------------Autocorrelations---------------

6 261.30 6 ................
................

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