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fonnesbeck / Introduction to Python.ipynb
Last active February 1, 2024 05:44
python/Introduction to Python.ipynb
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@fonnesbeck
fonnesbeck / Creating Interactive Visualizations with Bokeh.ipynb
Last active August 16, 2023 16:26
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fonnesbeck / log.txt
Created May 23, 2023 16:48
VSCode logging for remote extension installation
2023-05-23 11:18:55.462 [warning] Via 'product.json#extensionEnabledApiProposals' extension 'ms-vscode.vscode-selfhost-test-provider' wants API proposal 'testContinuousRun' but that proposal DOES NOT EXIST. Likely, the proposal has been finalized (check 'vscode.d.ts') or was abandoned.
2023-05-23 11:18:55.794 [error] Extension 'github.copilot' appears in product.json but enables LESS API proposals than the extension wants.
package.json (LOSES): inlineCompletionsAdditions, terminalDataWriteEvent
product.json (WINS): inlineCompletionsAdditions
2023-05-23 11:18:55.848 [info] Invoking resolveAuthority(attached-container)...
2023-05-23 11:18:55.849 [info] [LocalProcess0][resolveAuthority(attached-container,1)][0ms] obtaining proxy...
2023-05-23 11:18:55.849 [info] [LocalProcess0][resolveAuthority(attached-container,1)][0ms] invoking...
2023-05-23 11:18:56.852 [info] [LocalProcess0][resolveAuthority(attached-container,1)][1004ms] waiting...
2023-05-23 11:18:57.854 [info] [LocalProcess0][resolveAuthority(attached-co
@fonnesbeck
fonnesbeck / Covariate Model-First_Paper.ipynb
Created October 25, 2019 18:53
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fonnesbeck / pymc.md
Created January 16, 2015 20:42

PyMC

Markov chain Monte Carlo in Python

Chris Fonnesbeck

Vanderbilt Department of Biostatistics

Vanderbilt Center for Quantitative Sciences

Vanderbilt Evidence-based Practice Center

@fonnesbeck
fonnesbeck / Weibull Survival.ipynb
Created August 3, 2016 20:49
Weibull Survival.ipynb
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fonnesbeck / 3. Plotting and Visualization.ipynb
Created June 24, 2013 14:31
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fonnesbeck / Simple Measles Model (PyMC 2).ipynb
Last active May 12, 2022 11:48
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fonnesbeck / hmm.py
Created March 25, 2010 00:01
Hidden Markov model in PyMC
import numpy as np
import pymc
import pdb
def unconditionalProbability(Ptrans):
"""Compute the unconditional probability for the states of a
Markov chain."""
m = Ptrans.shape[0]
@fonnesbeck
fonnesbeck / Introduction to Jupyter Notebooks.ipynb
Created April 22, 2016 21:10
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