This table contains the latest execution statistics.
https://python.quantecon.org/aiyagari.htmlhttps://python.quantecon.org/ar1_bayes.htmlhttps://python.quantecon.org/ar1_turningpts.htmlhttps://python.quantecon.org/back_prop.htmlhttps://python.quantecon.org/bayes_nonconj.htmlhttps://python.quantecon.org/cake_eating_numerical.htmlhttps://python.quantecon.org/cake_eating_problem.htmlhttps://python.quantecon.org/career.htmlhttps://python.quantecon.org/cass_koopmans_1.htmlhttps://python.quantecon.org/cass_koopmans_2.htmlhttps://python.quantecon.org/coleman_policy_iter.htmlhttps://python.quantecon.org/complex_and_trig.htmlhttps://python.quantecon.org/cross_product_trick.htmlhttps://python.quantecon.org/egm_policy_iter.htmlhttps://python.quantecon.org/eig_circulant.htmlhttps://python.quantecon.org/exchangeable.htmlhttps://python.quantecon.org/finite_markov.htmlhttps://python.quantecon.org/ge_arrow.htmlhttps://python.quantecon.org/geom_series.htmlhttps://python.quantecon.org/harrison_kreps.htmlhttps://python.quantecon.org/heavy_tails.htmlhttps://python.quantecon.org/hoist_failure.htmlhttps://python.quantecon.org/house_auction.htmlhttps://python.quantecon.org/ifp.htmlhttps://python.quantecon.org/ifp_advanced.htmlhttps://python.quantecon.org/imp_sample.htmlhttps://python.quantecon.org/intro.htmlhttps://python.quantecon.org/inventory_dynamics.htmlhttps://python.quantecon.org/jv.htmlhttps://python.quantecon.org/kalman.htmlhttps://python.quantecon.org/kalman_2.htmlhttps://python.quantecon.org/kesten_processes.htmlhttps://python.quantecon.org/lagrangian_lqdp.htmlhttps://python.quantecon.org/lake_model.htmlhttps://python.quantecon.org/likelihood_bayes.htmlhttps://python.quantecon.org/likelihood_ratio_process.htmlhttps://python.quantecon.org/linear_algebra.htmlhttps://python.quantecon.org/linear_models.htmlhttps://python.quantecon.org/lln_clt.htmlhttps://python.quantecon.org/lp_intro.htmlhttps://python.quantecon.org/lq_inventories.htmlhttps://python.quantecon.org/lqcontrol.htmlhttps://python.quantecon.org/markov_asset.htmlhttps://python.quantecon.org/markov_perf.htmlhttps://python.quantecon.org/mccall_correlated.htmlhttps://python.quantecon.org/mccall_fitted_vfi.htmlhttps://python.quantecon.org/mccall_model.htmlhttps://python.quantecon.org/mccall_model_with_separation.htmlhttps://python.quantecon.org/mccall_q.htmlhttps://python.quantecon.org/mix_model.htmlhttps://python.quantecon.org/mle.htmlhttps://python.quantecon.org/multi_hyper.htmlhttps://python.quantecon.org/multivariate_normal.htmlhttps://python.quantecon.org/navy_captain.htmlhttps://python.quantecon.org/newton_method.htmlhttps://python.quantecon.org/odu.htmlhttps://python.quantecon.org/ols.htmlhttps://python.quantecon.org/opt_transport.htmlhttps://python.quantecon.org/optgrowth.htmlhttps://python.quantecon.org/optgrowth_fast.htmlhttps://python.quantecon.org/pandas_panel.htmlhttps://python.quantecon.org/perm_income.htmlhttps://python.quantecon.org/perm_income_cons.htmlhttps://python.quantecon.org/prob_matrix.htmlhttps://python.quantecon.org/prob_meaning.htmlhttps://python.quantecon.org/qr_decomp.htmlhttps://python.quantecon.org/rand_resp.htmlhttps://python.quantecon.org/rational_expectations.htmlhttps://python.quantecon.org/re_with_feedback.htmlhttps://python.quantecon.org/samuelson.htmlhttps://python.quantecon.org/scalar_dynam.htmlhttps://python.quantecon.org/schelling.htmlhttps://python.quantecon.org/short_path.htmlhttps://python.quantecon.org/sir_model.htmlhttps://python.quantecon.org/.htmlhttps://python.quantecon.org/svd_intro.htmlhttps://python.quantecon.org/troubleshooting.htmlhttps://python.quantecon.org/two_auctions.htmlhttps://python.quantecon.org/uncertainty_traps.htmlhttps://python.quantecon.org/util_rand_resp.htmlhttps://python.quantecon.org/var_dmd.htmlhttps://python.quantecon.org/von_neumann_model.htmlhttps://python.quantecon.org/wald_friedman.htmlhttps://python.quantecon.org/wealth_dynamics.htmlhttps://python.quantecon.org/zreferences.html|Document|Modified|Method|Run Time (s)|Status| |:------------------:|:------------------:|:------------------:|:------------------:|:------------------:| |aiyagari|2024-03-17 23:37|cache|26.07|✅| |ar1_bayes|2024-03-17 23:44|cache|424.14|✅| |ar1_turningpts|2024-03-17 23:45|cache|43.07|✅| |back_prop|2024-03-17 23:46|cache|74.86|✅| |bayes_nonconj|2024-03-18 00:57|cache|4268.17|✅| |cake_eating_numerical|2024-03-18 00:57|cache|28.8|✅| |cake_eating_problem|2024-03-18 00:57|cache|2.3|✅| |career|2024-03-18 00:58|cache|18.33|✅| |cass_koopmans_1|2024-03-18 00:58|cache|10.78|✅| |cass_koopmans_2|2024-03-18 00:58|cache|8.87|✅| |coleman_policy_iter|2024-03-18 00:58|cache|18.42|✅| |complex_and_trig|2024-03-18 00:59|cache|4.02|✅| |cross_product_trick|2024-03-18 00:59|cache|1.01|✅| |egm_policy_iter|2024-03-18 00:59|cache|6.7|✅| |eig_circulant|2024-03-18 00:59|cache|5.03|✅| |exchangeable|2024-03-18 00:59|cache|10.19|✅| |finite_markov|2024-03-18 00:59|cache|11.51|✅| |ge_arrow|2024-03-18 00:59|cache|2.33|✅| |geom_series|2024-03-18 00:59|cache|4.44|✅| |harrison_kreps|2024-03-18 00:59|cache|8.73|✅| |heavy_tails|2024-03-18 00:59|cache|1.16|✅| |hoist_failure|2024-03-18 01:01|cache|76.95|✅| |house_auction|2024-03-18 01:01|cache|7.83|✅| |ifp|2024-03-18 01:02|cache|54.74|✅| |ifp_advanced|2024-03-18 01:02|cache|31.32|✅| |imp_sample|2024-03-18 01:07|cache|276.63|✅| |intro|2024-03-18 00:59|cache|1.16|✅| |inventory_dynamics|2024-03-18 01:07|cache|12.12|✅| |jv|2024-03-18 01:07|cache|19.55|✅| |kalman|2024-03-18 01:08|cache|12.66|✅| |kalman_2|2024-03-18 01:08|cache|29.48|✅| |kesten_processes|2024-03-18 01:09|cache|52.98|✅| |lagrangian_lqdp|2024-03-18 01:09|cache|22.33|✅| |lake_model|2024-03-18 01:10|cache|20.39|✅| |likelihood_bayes|2024-03-18 01:11|cache|49.25|✅| |likelihood_ratio_process|2024-03-18 01:11|cache|10.66|✅| |linear_algebra|2024-03-18 01:11|cache|3.0|✅| |linear_models|2024-03-18 01:11|cache|12.87|✅| |lln_clt|2024-03-18 01:11|cache|14.52|✅| |lp_intro|2024-03-18 01:11|cache|2.07|✅| |lq_inventories|2024-03-18 01:12|cache|22.91|✅| |lqcontrol|2024-03-18 01:12|cache|10.69|✅| |markov_asset|2024-03-18 01:12|cache|11.33|✅| |markov_perf|2024-03-18 01:12|cache|9.74|✅| |mccall_correlated|2024-03-18 01:14|cache|92.87|✅| |mccall_fitted_vfi|2024-03-18 01:14|cache|12.59|✅| |mccall_model|2024-03-18 01:14|cache|20.77|✅| |mccall_model_with_separation|2024-03-18 01:15|cache|12.52|✅| |mccall_q|2024-03-18 01:15|cache|24.59|✅| |mix_model|2024-03-18 01:16|cache|36.87|✅| |mle|2024-03-18 01:16|cache|6.11|✅| |multi_hyper|2024-03-18 01:16|cache|25.66|✅| |multivariate_normal|2024-03-18 01:16|cache|5.66|✅| |navy_captain|2024-03-18 01:17|cache|34.81|✅| |newton_method|2024-03-18 01:18|cache|87.76|✅| |odu|2024-03-18 01:19|cache|59.03|✅| |ols|2024-03-18 01:20|cache|17.31|✅| |opt_transport|2024-03-18 01:20|cache|26.47|✅| |optgrowth|2024-03-18 01:21|cache|83.05|✅| |optgrowth_fast|2024-03-18 01:22|cache|29.25|✅| |pandas_panel|2024-03-18 01:22|cache|6.19|✅| |perm_income|2024-03-18 01:22|cache|4.82|✅| |perm_income_cons|2024-03-18 01:22|cache|12.02|✅| |prob_matrix|2024-03-18 01:23|cache|18.12|✅| |prob_meaning|2024-03-18 01:24|cache|75.82|✅| |qr_decomp|2024-03-18 01:24|cache|1.55|✅| |rand_resp|2024-03-18 01:24|cache|3.05|✅| |rational_expectations|2024-03-18 01:24|cache|8.84|✅| |re_with_feedback|2024-03-18 01:24|cache|12.87|✅| |samuelson|2024-03-18 01:25|cache|18.19|✅| |scalar_dynam|2024-03-18 01:25|cache|4.38|✅| |schelling|2024-03-18 01:25|cache|3.1|✅| |short_path|2024-03-18 01:25|cache|1.33|✅| |sir_model|2024-03-18 01:25|cache|3.79|✅| |status|2024-03-18 00:59|cache|1.16|✅| |svd_intro|2024-03-18 01:25|cache|1.69|✅| |troubleshooting|2024-03-18 00:59|cache|1.16|✅| |two_auctions|2024-03-18 01:25|cache|17.18|✅| |uncertainty_traps|2024-03-18 01:25|cache|3.3|✅| |util_rand_resp|2024-03-18 01:25|cache|3.61|✅| |var_dmd|2024-03-18 00:59|cache|1.16|✅| |von_neumann_model|2024-03-18 01:25|cache|2.93|✅| |wald_friedman|2024-03-18 01:26|cache|17.4|✅| |wealth_dynamics|2024-03-18 01:26|cache|43.62|✅| |zreferences|2024-03-18 00:59|cache|1.16|✅|
These lectures are built on linux
instances through github actions
and amazon web services (aws)
to
enable access to a gpu
. These lectures are built on a p3.2xlarge
that has access to 8 vcpu's
, a V100 NVIDIA Tesla GPU
, and 61 Gb
of memory.