4 ms·
I'm curious what resources you found useful to learn stats modelling and what sorts of approaches have been useful. On one hand, it's almost a tautoloy that sp
by Eridrus 8y ago
I'm curious what resources you found useful to learn stats modelling and what sorts of approaches have been useful.
On one hand, it's almost a tautoloy that specific models should be better than general models, but I worked on some 2d time series classification with a statistician and afterwards, for kicks, I replaced the entire thing with a CNN+LSTM and it worked just as well as the whole complicated model he had come up with.
- RA_Fisher 8y agoI highly recommend this econometrics text for getting started with statistics: https://www.amazon.com/Principles-Econometrics-5th-Carter-Hill-ebook/dp/B07BNZ6MWM https://www.amazon.com/Principles-Econometrics-5th-Carter-Hi... For modeling I found Wooldridge's panel and cross-section data book very useful: https://www.amazon.com/Econometric-Analysis-Cross-Section-Panel/dp/0262232588 https://www.amazon.com/Econometric-Analysis-Cross-Section-Pa... Greene is a really useful reference text: https://www.amazon.com/Econometric-Analysis-8th-William-Greene/dp/0134461363 https://www.amazon.com/Econometric-Analysis-8th-William-Gree... For advanced stats theory, I recommend Casella and Berger https://www.amazon.com/Statistical-Inference-George-Casella/dp/0534243126 https://www.amazon.com/Statistical-Inference-George-Casella/... Hope that helps! The more specific a model can be made to the problem at hand, the better it'll perform. Supervised ML models are great starting / baseline models.
- tomrod 8y agoI second Wooldridge. Greene I found to be much denser without providing much additional insight. It is a popular MS/PhD entry text though. I add any of Ken Train's work to this mix, especially on estimating discrete choice theory.