Merge pull request #790 from amas0/fix-documentation-links

WardBrian · web-flow · commit f4e233b6f0a0 · 2025-05-05T09:34:31.000-04:00
Fix documentation links
diff --git a/docsrc/community.rst b/docsrc/community.rst
@@ -24,7 +24,7 @@ Software
   with yearly, weekly, and daily seasonality, plus holiday effects.
 
 - `ArviZ <https://github.com/arviz-devs/arviz>`__ A Python package (with a
-  `Julia interface <https://julia.arviz.org/stable/>`_) for exploratory analysis of
+  `Julia interface <https://julia.arviz.org/ArviZ/stable/>`_) for exploratory analysis of
   Bayesian models. Includes functions for posterior analysis, data storage,
   model checking, comparison and diagnostics.
 
diff --git a/docsrc/users-guide/examples/MCMC Sampling.ipynb b/docsrc/users-guide/examples/MCMC Sampling.ipynb
@@ -21,7 +21,7 @@
     "generated quantities variables, reported on the constrained scale.\n",
     "\n",
     "The [CmdStanModel sample](https://mc-stan.org/cmdstanpy/api.html#cmdstanpy.CmdStanModel.sample) method\n",
-    "wraps the CmdStan [sample](https://mc-stan.org/docs/cmdstan-guide/mcmc-config.html) method.\n",
+    "wraps the CmdStan [sample](https://mc-stan.org/docs/cmdstan-guide/mcmc_config.html#running-the-sampler) method.\n",
     "Underlyingly, the CmdStan outputs are a set of per-chain Stan CSV files.\n",
     "In addition to the resulting sample, reported as one row per draw,\n",
     "the Stan CSV files encode information about the inference engine configuration\n",
diff --git a/docsrc/users-guide/examples/Run Generated Quantities.ipynb b/docsrc/users-guide/examples/Run Generated Quantities.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#  Generating new quantities of interest.\n",
+    "#  Generating new quantities of interest\n",
     "\n",
     "\n",
     "The [generated quantities block](https://mc-stan.org/docs/reference-manual/program-block-generated-quantities.html)\n",
diff --git a/docsrc/users-guide/examples/VI as Sampler Inits.ipynb b/docsrc/users-guide/examples/VI as Sampler Inits.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "In this example we show how to use the parameter estimates return by Stan's variational inference algorithms\n",
     "[pathfinder ](https://mc-stan.org/docs/cmdstan-guide/pathfinder-config.html)  and \n",
-    "[ADVI ](https://mc-stan.org/docs/cmdstan-guide/variational-config.html) \n",
+    "[ADVI ](https://mc-stan.org/docs/cmdstan-guide/variational_config.html) \n",
     "as the initial parameter values for Stan's NUTS-HMC sampler.\n",
     "By default, the sampler algorithm randomly initializes all model parameters in the range uniform\\[-2, 2\\].  When the true parameter value is outside of this range, starting from the estimates from Pathfinder and ADVI will speed up and improve adaptation.\n",
     "\n",
diff --git a/docsrc/users-guide/examples/Variational Inference.ipynb b/docsrc/users-guide/examples/Variational Inference.ipynb
@@ -30,7 +30,7 @@
     "### Example: variational inference for model ``bernoulli.stan``\n",
     "\n",
     "The [CmdStanModel variational](https://mc-stan.org/cmdstanpy/api.html#cmdstanpy.CmdStanModel.variational) method\n",
-    "wraps the CmdStan [variational](https://mc-stan.org/docs/cmdstan-guide/variational-config.html) method."
+    "wraps the CmdStan [variational](https://mc-stan.org/docs/cmdstan-guide/variational_config.html) method."
    ]
   },
   {
@@ -56,7 +56,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The class [`CmdStanVB`](https://mc-stan.org/cmdstanpy/api.html#cmdstanvb) provides the following properties to access information about the parameter names, estimated means, and the sample:\n",
+    "The [CmdStanVB](https://mc-stan.org/cmdstanpy/api.html#cmdstanvb) object provides the following properties to access information about the parameter names, estimated means, and the sample:\n",
     "\n",
     "  + `column_names` - list of column names\n",
     "  + `columns` - number of columns\n",
diff --git a/docsrc/users-guide/hello_world.rst b/docsrc/users-guide/hello_world.rst
@@ -115,7 +115,7 @@ Accessing the results
 ^^^^^^^^^^^^^^^^^^^^^
 
 The sampler outputs are the set of per-chain
-`Stan CSV files <https://mc-stan.org/docs/cmdstan-guide/stan-csv.html>`__,
+`Stan CSV files <https://mc-stan.org/docs/cmdstan-guide/stan_csv_apdx.html>`__,
 a non-standard CSV file format.
 Each data row of the Stan CSV file contains the per-iteration estimate of the Stan model
 parameters, transformed parameters,  and generated quantities variables.
@@ -200,7 +200,7 @@ all model parameters and quantities of interest in a pandas.DataFrame:
 
 
 CmdStan is distributed with a second posterior analysis utility
-`diagnose <https://mc-stan.org/docs/cmdstan-guide/diagnose.html>`__
+`diagnose <https://mc-stan.org/docs/cmdstan-guide/diagnose_utility.html>`__
 which analyzes the per-draw sampler parameters across all chains
 looking for potential problems which indicate that the sample
 isn't a representative sample from the posterior.
diff --git a/docsrc/users-guide/outputs.rst b/docsrc/users-guide/outputs.rst
@@ -7,7 +7,7 @@ CSV File Outputs
 ----------------
 
 Underlyingly, the CmdStan outputs are a set of per-chain
-`Stan CSV files <https://mc-stan.org/docs/cmdstan-guide/stan-csv.html#mcmc-sampler-csv-output>`__.
+`Stan CSV files <https://mc-stan.org/docs/cmdstan-guide/stan_csv_apdx.html#mcmc-sampler-csv-output>`__.
 The filenames follow the template '<model_name>-<YYYYMMDDHHMMSS>-<chain_id>'
 plus the file suffix '.csv'.
 CmdStanPy also captures the per-chain console and error messages.
diff --git a/docsrc/users-guide/overview.rst b/docsrc/users-guide/overview.rst
@@ -10,12 +10,12 @@ With CmdStanPy, you can:
 
 + Do inference on the model conditioned on the data, using one of Stan inference algorithms
 
-    + Exact Bayesian estimation using the `NUTS-HMC sampler <https://mc-stan.org/docs/reference-manual/hmc.html>`__.
+    + Exact Bayesian estimation using the `NUTS-HMC sampler <https://mc-stan.org/docs/reference-manual/mcmc.html#hamiltonian-monte-carlo>`__.
 
     + Approximate Bayesian estimation algorithms `Pathfinder <https://mc-stan.org/docs/reference-manual/pathfinder.html>`__
-      and `ADVI <https://mc-stan.org/docs/reference-manual/vi-algorithms.html>`__.
+      and `ADVI <https://mc-stan.org/docs/reference-manual/variational.html>`__.
 
-    + MAP estimation by `optimization <https://mc-stan.org/docs/reference-manual/optimization-algorithms.html>`__.
+    + MAP estimation by `optimization <https://mc-stan.org/docs/reference-manual/optimization.html>`__.
 
 + Generate new quantities of interest from a model given an existing sample.
 
diff --git a/docsrc/users-guide/workflow.rst b/docsrc/users-guide/workflow.rst
@@ -129,7 +129,7 @@ For each CmdStan inference method, there is a corresponding method on the :class
 An example of each is provided in the `next section <examples.rst>`__.
 
 * The :meth:`~CmdStanModel.sample` method runs Stan's
-  `HMC-NUTS sampler <https://mc-stan.org/docs/reference-manual/hamiltonian-monte-carlo.html>`__.
+  `HMC-NUTS sampler <https://mc-stan.org/docs/reference-manual/mcmc.html#hamiltonian-monte-carlo>`__.
 
   It returns a :class:`CmdStanMCMC` object which contains
   a sample from the posterior distribution of the model conditioned on the data.
@@ -141,12 +141,12 @@ An example of each is provided in the `next section <examples.rst>`__.
   a sample from a Gaussian approximation the posterior distribution.
 
 * The :meth:`~CmdStanModel.variational` method runs Stan's
-  `Automatic Differentiation Variational Inference (ADVI) algorithm <https://mc-stan.org/docs/reference-manual/vi-algorithms-chapter.html>`__.
+  `Automatic Differentiation Variational Inference (ADVI) algorithm <https://mc-stan.org/docs/reference-manual/variational.html>`__.
 
   It returns a :class:`CmdStanVB` object which contains an approximation the posterior distribution.
 
 * The :meth:`~CmdStanModel.optimize` runs one of Stan's
-  `optimization algorithms <https://mc-stan.org/docs/reference-manual/optimization-algorithms-chapter.html>`__
+  `optimization algorithms <https://mc-stan.org/docs/reference-manual/optimization.html>`__
   to find a mode of the density specified by the Stan program.
 
   It returns a :class:`CmdStanMLE` object.
@@ -155,7 +155,7 @@ An example of each is provided in the `next section <examples.rst>`__.
   `generate_quantities method <https://mc-stan.org/docs/cmdstan-guide/standalone-generate-quantities.html>`__.
   which generates additional quantities of interest from a mode. Its take an existing fit as input and
   uses the parameter estimates in the fit to run the Stan program's
-  `generated quantities block <https://mc-stan.org/docs/reference-manual/program-block-generated-quantities.html>`__.
+  `generated quantities block <https://mc-stan.org/docs/reference-manual/blocks.html#program-block-generated-quantities>`__.
 
   It returns a :class:`CmdStanGQ` object.
 
