Description Usage Arguments Value Author(s) References See Also Examples

The time series plot and the sample ACF of the standardized residuals are plotted. Also, a portmanteau test for detecting residual correlations in the standardized residuals are carried out.

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`object` |
a fitted TAR model output from the tar function |

`gof.lag` |
number of lags of ACF to be examined |

`col` |
color of the lines flagging outliers, etc. |

`xlab` |
x labels for the plots |

`...` |
any additional user-supplied options to be passed to the acf function |

Side effects: plot the time-series plot of the standardized residuals, their sample ACF and portmanteau test for residual autocorrelations in the standardized errors.

Kung-Sik Chan

"Time Series Analysis, with Applications in R" by J.D. Cryer and K.S. Chan

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```
Attaching package: 'TSA'
The following objects are masked from 'package:stats':
acf, arima
The following object is masked from 'package:utils':
tar
time series included in this analysis is: log(prey.eq)
SETAR(2, 1 , 4 ) model delay = 3
estimated threshold = 4.661 from a Minimum AIC fit with thresholds
searched from the 17 percentile to the 81 percentile of all data.
The estimated threshold is the 56.6 percentile of
all data.
lower regime:
Residual Standard Error=0.2341
R-Square=0.9978
F-statistic (df=2, 28)=6355.76
p-value=0
Estimate Std.Err t-value Pr(>|t|)
intercept-log(prey.eq) 0.2621 0.3156 0.8305 0.4133
lag1-log(prey.eq) 1.0175 0.0704 14.4455 0.0000
(unbiased) RMS
0.05479
with no of data falling in the regime being
log(prey.eq) 30
(max. likelihood) RMS for each series (denominator=sample size in the regime)
log(prey.eq) 0.05114
upper regime:
Residual Standard Error=0.2676
R-Square=0.9971
F-statistic (df=5, 18)=1253.556
p-value=0
Estimate Std.Err t-value Pr(>|t|)
intercept-log(prey.eq) 4.1986 1.2841 3.2697 0.0043
lag1-log(prey.eq) 0.7081 0.2023 3.5005 0.0026
lag2-log(prey.eq) -0.3009 0.3118 -0.9648 0.3474
lag3-log(prey.eq) 0.2788 0.4063 0.6861 0.5014
lag4-log(prey.eq) -0.6113 0.2726 -2.2427 0.0377
(unbiased) RMS
0.07158
with no of data falling in the regime being
23
(max. likelihood) RMS for each series (denominator=sample size in the regime)
0.05602
Nominal AIC is 10.92
```

TSA documentation built on July 2, 2018, 1:04 a.m.

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