- This exercise is about regularization priors. In the code that generates the data, change order=2 to another value, such as order=5. Then, fit model_p and plot the resulting curve. Repeat this, but now using a prior for beta with sd=100 instead of sd=1 and plot the resulting curve. How are both curves different? Try this out with sd=np.array([10, 0.1, 0.1, 0.1, 0.1]), too.
- Repeat the previous exercise but increase the amount of data to 500 data points.
- Fit a cubic model (order 3), compute WAIC and LOO, plot the results, and compare them with the linear and quadratic models.
- Use pm.sample_posterior_predictive() to rerun the PPC example, but this time, plot the values of y instead of the values of the mean.
- Read and run the posterior predictive example from PyMC3's documentation at https://pymc-devs.github.io/pymc3/notebooks/posterior_predictive.html. Pay special...
United States
Great Britain
India
Germany
France
Canada
Russia
Spain
Brazil
Australia
Singapore
Hungary
Ukraine
Luxembourg
Estonia
Lithuania
South Korea
Turkey
Switzerland
Colombia
Taiwan
Chile
Norway
Ecuador
Indonesia
New Zealand
Cyprus
Denmark
Finland
Poland
Malta
Czechia
Austria
Sweden
Italy
Egypt
Belgium
Portugal
Slovenia
Ireland
Romania
Greece
Argentina
Netherlands
Bulgaria
Latvia
South Africa
Malaysia
Japan
Slovakia
Philippines
Mexico
Thailand