Question
The Box–Jenkins method can be used to select the parameters of an ARIMA (“uh-REE-muh”) model for data indexed by this variable. For 10 points each:
[10e] Name this variable plotted on the x-axis of namesake “series” of data. Stochastic processes like Brownian motion and stock market returns are often indexed by this variable.
ANSWER: time [prompt on t]
[10h] The Box–Jenkins method uses a variant of correlation denoted by this adjective, which first regresses off data at shorter lags. Similarly, this adjective denotes a regression diagnostics method that plots the response against the added variable, after regressing off all other variables.
ANSWER: partial [accept partial correlation or partial autocorrelation function; accept partial regression]
[10m] An early step of the Box–Jenkins method is to transform or apply differencing to better attain this property. A time series with this property has the same joint probability at any point in time.
ANSWER: stationary [or stationarity]
<Rutgers A, Other Science>
Summary
California | 2025-02-01 | Y | 3 | 10.00 | 100% | 0% | 0% |
Florida | 2025-02-01 | Y | 3 | 13.33 | 100% | 33% | 0% |
Great Lakes | 2025-02-01 | Y | 6 | 10.00 | 100% | 0% | 0% |
Midwest | 2025-02-01 | Y | 6 | 10.00 | 83% | 17% | 0% |
North | 2025-02-01 | Y | 3 | 6.67 | 67% | 0% | 0% |
Northeast | 2025-02-01 | Y | 5 | 8.00 | 80% | 0% | 0% |
Overflow | 2025-02-01 | Y | 5 | 10.00 | 100% | 0% | 0% |
South Central | 2025-02-01 | Y | 2 | 10.00 | 100% | 0% | 0% |
Southeast | 2025-02-01 | Y | 4 | 7.50 | 75% | 0% | 0% |
UK | 2025-02-01 | Y | 10 | 12.00 | 100% | 10% | 10% |
Upper Mid-Atlantic | 2025-02-01 | Y | 8 | 12.50 | 88% | 38% | 0% |
Upstate NY | 2025-02-01 | Y | 3 | 10.00 | 67% | 33% | 0% |
Data
Georgetown A | Northwestern A | 10 | 0 | 0 | 10 |
Notre Dame B | Georgetown B | 10 | 0 | 0 | 10 |
Notre Dame A | Iowa | 10 | 0 | 0 | 10 |
Northwestern B | Stanford B | 10 | 0 | 0 | 10 |
Notre Dame C | Purdue | 10 | 0 | 0 | 10 |