Stata has always been strong on both, and we have added more features.
#Stata mp vs ic 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.
#Stata mp vs ic windows#
#Stata mp vs ic series#
Flexible nonparametric series regression.Extended regression models (ERMs) for panel data.Bayesian predictions, multiple chains, and more.Revamped and expanded choice modeling (margins works everywhere).Reproducible and automatically updating reports.Lasso, both for prediction and for inference.
Or you can scroll down and read my comments, which I hope are more entertaining even if they are less informative. If you click on a highlight, we will spirit you away to our website, where we will describe the feature in a dry but information-dense way. It ranges from lasso to Python and from multiple datasets in memory to multiple chains in Bayesian analysis. Stata 16 is a big release, which our releases usually are. We just announced the release of Stata 16.