Here’s a link to the manual so you can judge for yourself. We tell you and we show you, with examples and workflows.
Stata update how to#
The real problem was that we never told you how to use the reporting features. I think what’s important is another aspect of what we did. I don’t want to downplay the additions, but neither do I want to discuss them.
Stata has always been strong on both, and we have added more features.
Stata update update#
The inelegant title above is trying to say (1) reports that reproduce themselves just as they were originally and (2) reports that, when run again, update themselves by running the analysis on the latest data. Reproducible and automatically updating reports I specified one variable of special interest in the example, but you can specify however many you wish.Ģ. Reported will be the coefficient and its standard error for x1. Anyway, the inference calculations are robust to those errors. Another way to think about selection is that lasso estimates the variables to be selected and, as with all estimation, that is subject to error. I said earlier that they are correlated with the true variables, and they are. That’s not how the calculation is made because the variables lasso selects are not identical to the true variables that belong in the model. Then, conceptually but not actually, y will be fit on x1 and the variables lasso selects from x2-x999. Anyway, the lasso command is for prediction, and standard errors for the covariates it selects are not reported because they would be misleading.Ĭoncerning inference, we provide four lasso-based methods: double selection, cross-fit partialing out, and two more. If English is not your first language, by “works a treat”, I mean great. lasso will be unlikely to choose the covariates that belong in the true model, but it will choose covariates that are collinear with them, and that works a treat for prediction. Lasso will select the covariates from the x‘s specified and fit the model on them. By the way, when I say lasso, I mean lasso, elastic net, and square-root lasso, but if you want a features list, click the title. I suspect inference will be of more interest to our users, but we needed prediction to implement inference. There are two parts to our implementation of lasso: prediction and inference. Lasso, both for prediction and for inference Meanwhile, Mata matrices remain limited only by memory.ġ. Oh, and in Stata/MP, Stata matrices can now be up to 65,534 x 65,534, meaning you can fit models with over 65,000 right-hand-side variables.
Stata just works, and it uses less memory. set matsize 600Īnd if you do type it, you will be ignored. Buy the update, and you will never again have to type. It may not be enough to make you buy the release, but it will half tempt you. I added it because I suspect it will affect the most Stata users. Number 22 is not a link because it’s not a highlight.
Multiple datasets in memory, meaning frames.
Stata update series#
0 kommentar(er)
