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🎨 Update plots from pymc to arviz dependencies & replace param sd with sigma
1 parent 0975dfb commit 0778030

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8 files changed

+290
-324
lines changed

8 files changed

+290
-324
lines changed

examples/survival_analysis/bayes_param_survival_pymc3.ipynb

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examples/survival_analysis/censored_data.ipynb

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examples/survival_analysis/cox_model.ipynb

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examples/survival_analysis/survival_analysis.ipynb

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}
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],
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"source": [
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"pm.plot_posterior(trace, var_names=[\"beta\"], color=\"#87ceeb\");"
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"az.plot_posterior(trace, var_names=[\"beta\"], color=\"#87ceeb\");"
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]
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},
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{
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}
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],
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"source": [
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"pm.autocorrplot(trace, var_names=[\"beta\"]);"
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"az.plot_autocorr(trace, var_names=[\"beta\"]);"
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]
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},
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{
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}
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],
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"source": [
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"pm.forestplot(time_varying_trace, var_names=[\"beta\"]);"
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"az.plot_forest(time_varying_trace, var_names=[\"beta\"]);"
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.2"
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"version": "3.8.5"
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}
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},
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"nbformat": 4,

examples/survival_analysis/weibull_aft.ipynb

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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.3"
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"version": "3.8.5"
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},
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"toc": {
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"base_numbering": 1,

examples/time_series/AR.ipynb

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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.8.2 64-bit ('pymc3': conda)",
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"display_name": "Python (PyMC3 Dev)",
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"language": "python",
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"name": "python38264bitpymc3conda8b8223a2f9874eff9bd3e12d36ed2ca2"
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"name": "pymc3-dev"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.2-final"
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"version": "3.8.5"
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},
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"name": "AR.ipynb"
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},

examples/time_series/Euler-Maruyama_and_SDEs.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.7"
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"version": "3.8.5"
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},
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"latex_envs": {
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"bibliofile": "biblio.bib",

examples/time_series/MvGaussianRandomWalk_demo.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.7"
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"version": "3.8.5"
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}
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},
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"nbformat": 4,

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