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interpreting aic and bic in stata

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aic bic interpretation

This entry discusses a statistical issue that arises when using the Bayesian information criterion. (BIC) to compare models. Stata calculates BIC, assuming N = e(N)—we will explain—but sometimes it would be better if a different N were used. Commands that calculate BIC have an n() option, allowing you to specify the N to
mean that at least one of the VAR models considered by varsoc will not contain the lag specified in the constraint. Use var directly to obtain selection-order criteria with constraints on lags of the endogenous variables. noconstant suppresses the constant terms from the model. By default, constant terms are included.
The variables in the model 1 are selected using Stata command vselect whereas Model 2 using Stata command gsreg. You can also get the AIC value manually by first estimating the model, and then typing estat ic There are a number of other similar model selection criteria you can research (DIC, FIC, BPIC, etc.).
7 Nov 2015
In situations where there is a complex hierarchy, backward elimination can be run manually while taking account Variable selection tends to amplify the statistical significance of the variables that stay in the model. Variables . The Akaike Information Criterion (AIC) and the Bayes Information Criterion (BIC) are some other.
24 Jun 2009 Stata has two versions of AIC statistics, one used with -glm- and another -estat ic- The -estat ic- version does not adjust the log-likelihood and penalty term by the number of observations in the model, whereas the version used in -glm- does. ESTAT-IC AIC = -2LL + 2k = -2(LL-k) GLM AIC = -2LL + 2k
10 Sep 2007 Welcome to the fifth issue of e-Tutorial, the on-line help to Econ 508. This issue provides an introduction to model selection in Econometrics, focusing on Akaike (AIC) and Schwarz (SIC) Information Criteria. Data Set: The data set used in this tutorial was borrowed from Johnston and DiNardo's Econometric
Hello, I'm using Stata 12.1 for my dissertation and I have a problem with saving and using the information criterion which prevents me to get the results I.
26 Jul 2013
Model. Obs ll(null) ll(model) df. AIC. BIC . 615. -555.8545. -534.3616. 12. 1092.723. 1145.783. Note: N="Obs" used in calculating BIC; see [R] BIC note. The AIC indicates that the model including the site dummies fits the data better, whereas the BIC indicates the opposite. As is often the case, different model-selection criteria

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February 2018