Timeline for Time series estimation on specific lags in ARMA model
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
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| Jul 6, 2014 at 19:08 | comment | added | javlacalle |
You can obtain the AIC as AIC(fit, k = 2) and BIC as AIC(fit, k = log(length(x))); use logLik(fit) to extract the log-likelihood; t-statistics and p-values can be conveniently obtained using coeftest in package lmtest, require(lmtest); coeftest(fit); you may also be interested in confidence intervals for the parameter estimates, they can be obtained as confint(fit). The R-square is not that meaningful in the context of ARIMA models, see this post.
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| Jul 6, 2014 at 17:36 | comment | added | user49456 | another query is in R these codes do not provide values of P-values and t-statistics, BIC, SIC, R-square etc | |
| Jul 5, 2014 at 20:52 | comment | added | javlacalle |
The error says that there was a problem in the optimization algorithm, apparently the numerical gradient was not a finite value. You can try: 1) pass different initial values through the argument init; 2) use method="CSS" in the function arima. If you post the data, the output of dput(data.object), I could have a look at it.
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| Jul 5, 2014 at 19:39 | comment | added | user49456 | Thank You for your cooperation. Its means alot I am trying to understand and follow these steps. When I apply this command (arima) on my data, after applying it it gives an error "Error in optim(init[mask], armafn, method = optim.method, hessian = TRUE, : non-finite finite-difference value [1]" can you please explain wt does this error means? | |
| Jul 4, 2014 at 18:19 | history | answered | javlacalle | CC BY-SA 3.0 |