例句與造句

1. Most software that can generate the autocorrelation plot can also generate this confidence interval.
2. However, if the period is not known, the autocorrelation plot can help.
3. If there is significant seasonality, the autocorrelation plot should show spikes at lags equal to the period.
4. For higher-order autoregressive processes, the sample autocorrelation needs to be supplemented with a partial autocorrelation plot.
5. If the period is not known, an autocorrelation plot or spectral plot can be used to determine it.
6. It's difficult to find autocorrelation plot in a sentence. 用autocorrelation plot造句挺難的
7. We do this by placing the 95 % confidence interval for the sample autocorrelation function on the sample autocorrelation plot.
8. If the sample autocorrelation plot indicates that an AR model may be appropriate, then the sample partial autocorrelation plot is examined to help identify the order.
9. If the sample autocorrelation plot indicates that an AR model may be appropriate, then the sample partial autocorrelation plot is examined to help identify the order.
10. Partial autocorrelation plots ( Box and Jenkins, Chapter 3.2, 2008 ) are a commonly used tool for identifying the order of an autoregressive model.
11. One way to assess if the residuals from the Box Jenkins model follow the assumptions is to generate statistical graphics ( including an autocorrelation plot ) of the residuals.
12. This is usually determined by placing a 95 % confidence interval on the sample partial autocorrelation plot ( most software programs that generate sample autocorrelation plots also plot this confidence interval ).
13. This is usually determined by placing a 95 % confidence interval on the sample partial autocorrelation plot ( most software programs that generate sample autocorrelation plots also plot this confidence interval ).
14. For example, in time series analysis, a correlogram, also known as an "'autocorrelation plot "', is a plot of the sample autocorrelations r _ h \, versus h \, ( the time lags ).
15. An autocorrelation plot ( ACF ) can be used to identify seasonality, as it calculates the difference ( residual amount ) between a Y value and a lagged value of Y . The result gives some points where the two values are close together ( no seasonality ), but other points where there is a large discrepancy.