r*******g
发帖数: 1707 | 1 Matlab: more application in engineering(?) programming, also econometricians
like play with and write tricky estimators in matlab by themselves, rather
than in built-in commands
SAS: definitely the best in dealing with huge datasets, so very popular in
industry. it is not as statistically friendly as Stata, but more friendly than
Matlab. in short, it is a little hard but very powerful in datasets and most
industry.
Stata: convenient in estimation and graphs, but you can't change the built-in
est | z*i
发帖数: 58873 | 2 At least in econ consulting people use SAS and Stata most of the time.
SAS is not only good for handling big datasets. It is also good when you want
to manipulate the data and clean up the data. But personally i don't like the
regression functions in SAS. I think stata is much cleaner. Eviews is great as
well. All those packages are not hard to learn anyway. So unnecessary to sweat
about which to pick and use.
interface
econometricians
rather
in
friendly than
most
built-in
hehe);
this is
econ/b
【在 r*******g 的大作中提到】
: Matlab: more application in engineering(?) programming, also econometricians
: like play with and write tricky estimators in matlab by themselves, rather
: than in built-in commands
: SAS: definitely the best in dealing with huge datasets, so very popular in
: industry. it is not as statistically friendly as Stata, but more friendly than
: Matlab. in short, it is a little hard but very powerful in datasets and most
: industry.
: Stata: convenient in estimation and graphs, but you can't change the built-in
: est
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