From 48e46d68ea6b68db19df32e620791a2d91244543 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Thu, 13 May 2021 22:15:27 -0400
Subject: [PATCH 01/12] Refactoring ChiSquared distribution

---
 pymc3/distributions/continuous.py        | 18 +++++++++++++++++-
 pymc3/tests/test_distributions.py        |  1 -
 pymc3/tests/test_distributions_random.py |  8 +++++++-
 3 files changed, 24 insertions(+), 3 deletions(-)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index a2b9bd4f47..b5182826e2 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2602,6 +2602,21 @@ def logcdf(value, alpha, beta):
         )
 
 
+class ChiSquaredRV(RandomVariable):
+    name = "chi_squared"
+    ndim_supp = 0
+    ndims_params = [0]
+    dtype = "floatX"
+    _print_name = ("ChiSquared", "\\operatorname{ChiSquared}")
+
+    @classmethod
+    def rng_fn(cls, rng, nu, size=None):
+        return stats.chi2(nu, size=size, random_state=rng)
+
+
+chi_squared = ChiSquaredRV()
+
+
 class ChiSquared(Gamma):
     r"""
     :math:`\chi^2` log-likelihood.
@@ -2641,7 +2656,8 @@ class ChiSquared(Gamma):
         Degrees of freedom (nu > 0).
     """
 
-    def __init__(self, nu, *args, **kwargs):
+    @classmethod
+    def dist(cls, nu, *args, **kwargs):
         self.nu = nu = at.as_tensor_variable(floatX(nu))
         super().__init__(alpha=nu / 2.0, beta=0.5, *args, **kwargs)
 
diff --git a/pymc3/tests/test_distributions.py b/pymc3/tests/test_distributions.py
index 63466b7902..e47c41b596 100644
--- a/pymc3/tests/test_distributions.py
+++ b/pymc3/tests/test_distributions.py
@@ -1030,7 +1030,6 @@ def test_half_normal(self):
             lambda value, sigma: sp.halfnorm.logcdf(value, scale=sigma),
         )
 
-    @pytest.mark.xfail(reason="Distribution not refactored yet")
     def test_chi_squared(self):
         self.check_logp(
             ChiSquared,
diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index 82d4f4e091..74eb06cb2f 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -295,10 +295,16 @@ class TestStudentT(BaseTestCases.BaseTestCase):
     params = {"nu": 5.0, "mu": 0.0, "lam": 1.0}
 
 
-@pytest.mark.xfail(reason="This distribution has not been refactored for v4")
 class TestChiSquared(BaseTestCases.BaseTestCase):
     distribution = pm.ChiSquared
     params = {"nu": 2.0}
+    expected_rv_op_params = {"nu": 2.0}
+    reference_dist_params = {"df": 2.0}
+    reference_dist = seeded_numpy_distribution_builder("chisquare")
+    tests_to_run = [
+        "check_pymc_params_match_rv_op",
+        "check_pymc_draws_match_reference",
+    ]
 
 
 @pytest.mark.xfail(reason="This distribution has not been refactored for v4")

From 4de21920c9761a7e9acbc1a376a0dc3d6dfcf266 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Thu, 13 May 2021 22:26:39 -0400
Subject: [PATCH 02/12] Refactoring ChiSquared (minor edit)

---
 pymc3/distributions/continuous.py        | 1 +
 pymc3/tests/test_distributions_random.py | 1 +
 2 files changed, 2 insertions(+)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index b5182826e2..5f0d976eec 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2655,6 +2655,7 @@ class ChiSquared(Gamma):
     nu: int
         Degrees of freedom (nu > 0).
     """
+    rv_op = chi_squared
 
     @classmethod
     def dist(cls, nu, *args, **kwargs):
diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index 74eb06cb2f..72e5356c91 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -304,6 +304,7 @@ class TestChiSquared(BaseTestCases.BaseTestCase):
     tests_to_run = [
         "check_pymc_params_match_rv_op",
         "check_pymc_draws_match_reference",
+        "check_rv_size",
     ]
 
 

From 53c8cc85cb4434623e84127a53712a1e0b2523c7 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Thu, 13 May 2021 22:27:57 -0400
Subject: [PATCH 03/12] Refactoring Chisquared (another one-line change)

---
 pymc3/distributions/continuous.py        | 2 +-
 pymc3/tests/test_distributions_random.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index 5f0d976eec..496bea685b 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2659,7 +2659,7 @@ class ChiSquared(Gamma):
 
     @classmethod
     def dist(cls, nu, *args, **kwargs):
-        self.nu = nu = at.as_tensor_variable(floatX(nu))
+        nu = at.as_tensor_variable(floatX(nu))
         super().__init__(alpha=nu / 2.0, beta=0.5, *args, **kwargs)
 
 
diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index 72e5356c91..d99107120d 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -306,7 +306,7 @@ class TestChiSquared(BaseTestCases.BaseTestCase):
         "check_pymc_draws_match_reference",
         "check_rv_size",
     ]
-
+    
 
 @pytest.mark.xfail(reason="This distribution has not been refactored for v4")
 class TestExGaussian(BaseTestCases.BaseTestCase):

From ba3099b8da8a07ad1e241f14f1123849991ec8d4 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Thu, 20 May 2021 18:21:17 -0400
Subject: [PATCH 04/12] Trying to rebase/merge my branch with updated upstream
 v4

---
 pymc3/tests/test_distributions_random.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index d99107120d..72e5356c91 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -306,7 +306,7 @@ class TestChiSquared(BaseTestCases.BaseTestCase):
         "check_pymc_draws_match_reference",
         "check_rv_size",
     ]
-    
+
 
 @pytest.mark.xfail(reason="This distribution has not been refactored for v4")
 class TestExGaussian(BaseTestCases.BaseTestCase):

From be682a2e527799d87deb11fac026b37eecdcc544 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Thu, 20 May 2021 18:35:10 -0400
Subject: [PATCH 05/12] Using aesara chisquare op (r.f. PR #414) and renamed
 ChiSquared to ChiSquare

---
 docs/source/api/distributions/continuous.rst |  2 +-
 pymc3/distributions/__init__.py              |  4 ++--
 pymc3/distributions/continuous.py            | 22 ++++----------------
 pymc3/distributions/multivariate.py          |  4 ++--
 pymc3/gp/gp.py                               |  2 +-
 pymc3/tests/test_distributions.py            |  4 ++--
 pymc3/tests/test_distributions_random.py     |  5 ++---
 7 files changed, 14 insertions(+), 29 deletions(-)

diff --git a/docs/source/api/distributions/continuous.rst b/docs/source/api/distributions/continuous.rst
index 9222dcb797..3399ccf039 100644
--- a/docs/source/api/distributions/continuous.rst
+++ b/docs/source/api/distributions/continuous.rst
@@ -25,7 +25,7 @@ Continuous
    InverseGamma
    Weibull
    Lognormal
-   ChiSquared
+   ChiSquare
    Wald
    Pareto
    ExGaussian
diff --git a/pymc3/distributions/__init__.py b/pymc3/distributions/__init__.py
index 807b483712..ee51a8d351 100644
--- a/pymc3/distributions/__init__.py
+++ b/pymc3/distributions/__init__.py
@@ -27,7 +27,7 @@
     AsymmetricLaplace,
     Beta,
     Cauchy,
-    ChiSquared,
+    ChiSquare,
     ExGaussian,
     Exponential,
     Flat,
@@ -125,7 +125,7 @@
     "Bound",
     "Lognormal",
     "HalfStudentT",
-    "ChiSquared",
+    "ChiSquare",
     "HalfNormal",
     "Wald",
     "Pareto",
diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index c1d2869a54..02ccffa354 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -28,6 +28,7 @@
     BetaRV,
     WeibullRV,
     cauchy,
+    chisquare,
     exponential,
     gamma,
     gumbel,
@@ -87,7 +88,7 @@
     "Weibull",
     "HalfStudentT",
     "Lognormal",
-    "ChiSquared",
+    "ChiSquare",
     "HalfNormal",
     "Wald",
     "Pareto",
@@ -2548,22 +2549,7 @@ def logcdf(value, alpha, beta):
         )
 
 
-class ChiSquaredRV(RandomVariable):
-    name = "chi_squared"
-    ndim_supp = 0
-    ndims_params = [0]
-    dtype = "floatX"
-    _print_name = ("ChiSquared", "\\operatorname{ChiSquared}")
-
-    @classmethod
-    def rng_fn(cls, rng, nu, size=None):
-        return stats.chi2(nu, size=size, random_state=rng)
-
-
-chi_squared = ChiSquaredRV()
-
-
-class ChiSquared(Gamma):
+class ChiSquare(Gamma):
     r"""
     :math:`\chi^2` log-likelihood.
 
@@ -2601,7 +2587,7 @@ class ChiSquared(Gamma):
     nu: int
         Degrees of freedom (nu > 0).
     """
-    rv_op = chi_squared
+    rv_op = chisquare
 
     @classmethod
     def dist(cls, nu, *args, **kwargs):
diff --git a/pymc3/distributions/multivariate.py b/pymc3/distributions/multivariate.py
index 4eb6b01817..3bdce21e45 100644
--- a/pymc3/distributions/multivariate.py
+++ b/pymc3/distributions/multivariate.py
@@ -40,7 +40,7 @@
 
 from pymc3.aesaraf import floatX, intX
 from pymc3.distributions import transforms
-from pymc3.distributions.continuous import ChiSquared, Normal
+from pymc3.distributions.continuous import ChiSquare, Normal
 from pymc3.distributions.dist_math import bound, factln, logpow
 from pymc3.distributions.distribution import Continuous, Discrete
 from pymc3.distributions.special import gammaln, multigammaln
@@ -905,7 +905,7 @@ def WishartBartlett(name, S, nu, is_cholesky=False, return_cholesky=False, testv
         tril_testval = None
 
     c = at.sqrt(
-        ChiSquared("%s_c" % name, nu - np.arange(2, 2 + n_diag), shape=n_diag, testval=diag_testval)
+        ChiSquare("%s_c" % name, nu - np.arange(2, 2 + n_diag), shape=n_diag, testval=diag_testval)
     )
     pm._log.info("Added new variable %s_c to model diagonal of Wishart." % name)
     z = Normal("%s_z" % name, 0.0, 1.0, shape=n_tril, testval=tril_testval)
diff --git a/pymc3/gp/gp.py b/pymc3/gp/gp.py
index 17e232f0c2..31fbb41fe3 100644
--- a/pymc3/gp/gp.py
+++ b/pymc3/gp/gp.py
@@ -278,7 +278,7 @@ def _build_prior(self, name, X, reparameterize=True, **kwargs):
         cov = stabilize(self.cov_func(X))
         shape = infer_shape(X, kwargs.pop("shape", None))
         if reparameterize:
-            chi2 = pm.ChiSquared(name + "_chi2_", self.nu)
+            chi2 = pm.ChiSquare(name + "_chi2_", self.nu)
             v = pm.Normal(name + "_rotated_", mu=0.0, sigma=1.0, size=shape, **kwargs)
             f = pm.Deterministic(name, (at.sqrt(self.nu) / chi2) * (mu + cholesky(cov).dot(v)))
         else:
diff --git a/pymc3/tests/test_distributions.py b/pymc3/tests/test_distributions.py
index a0869edbc4..062663b1da 100644
--- a/pymc3/tests/test_distributions.py
+++ b/pymc3/tests/test_distributions.py
@@ -48,7 +48,7 @@
     Bound,
     Categorical,
     Cauchy,
-    ChiSquared,
+    ChiSquare,
     Constant,
     DensityDist,
     Dirichlet,
@@ -1032,7 +1032,7 @@ def test_half_normal(self):
 
     def test_chi_squared(self):
         self.check_logp(
-            ChiSquared,
+            ChiSquare,
             Rplus,
             {"nu": Rplusdunif},
             lambda value, nu: sp.chi2.logpdf(value, df=nu),
diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index df9b085402..2c44f44a53 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -277,9 +277,8 @@ class TestAsymmetricLaplace(BaseTestCases.BaseTestCase):
     params = {"kappa": 1.0, "b": 1.0, "mu": 0.0}
 
 
-@pytest.mark.xfail(reason="This distribution has not been refactored for v4")
-class TestChiSquared(BaseTestCases.BaseTestCase):
-    distribution = pm.ChiSquared
+class TestChiSquare(BaseTestCases.BaseTestCase):
+    distribution = pm.ChiSquare
     params = {"nu": 2.0}
     expected_rv_op_params = {"nu": 2.0}
     reference_dist_params = {"df": 2.0}

From dff62a192c6e7cf74f7307d8558c9fe8552176f5 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Sun, 30 May 2021 18:40:03 -0400
Subject: [PATCH 06/12] Added logpdf & logcdf to the ChiSquare class

---
 pymc3/distributions/continuous.py | 33 +++++++++++++++++++++++++++++++
 1 file changed, 33 insertions(+)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index 02ccffa354..040ae2ceb4 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2594,6 +2594,39 @@ def dist(cls, nu, *args, **kwargs):
         nu = at.as_tensor_variable(floatX(nu))
         super().__init__(alpha=nu / 2.0, beta=0.5, *args, **kwargs)
 
+    def logp(value, nu):
+        """
+        Calculate log-probability of ChiSquare distribution at specified value.
+
+        Parameters
+        ----------
+        value: numeric
+            Value(s) for which log-probability is calculated. If the log probabilities for multiple
+            values are desired the values must be provided in a numpy array or Aesara tensor
+
+        Returns
+        -------
+        TensorVariable
+        """
+        return Gamma.logpdf(value, nu/2, 2)
+
+    def logcdf(value, nu):
+        """
+        Compute the log of the cumulative distribution function for ChiSquare distribution
+        at the specified value.
+
+        Parameters
+        ----------
+        value: numeric or np.ndarray or `TensorVariable`
+            Value(s) for which log CDF is calculated. If the log CDF for
+            multiple values are desired the values must be provided in a numpy
+            array or `TensorVariable`.
+        Returns
+        -------
+        TensorVariable
+        """
+        return Gamma.logcdf(value, nu/2, 2)
+
 
 # TODO: Remove this once logpt for multiplication is working!
 class WeibullBetaRV(WeibullRV):

From e7ba22404f387f64b5b155388a810c8b2e8d564c Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Mon, 31 May 2021 07:43:55 -0400
Subject: [PATCH 07/12] Corrected function name

---
 pymc3/distributions/continuous.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index 040ae2ceb4..31b8557ee5 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2608,7 +2608,7 @@ def logp(value, nu):
         -------
         TensorVariable
         """
-        return Gamma.logpdf(value, nu/2, 2)
+        return Gamma.logp(value, nu/2, 2)
 
     def logcdf(value, nu):
         """

From 78ca870db2f86a9f7524f8bf0250af5a9849604b Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Tue, 1 Jun 2021 23:37:06 -0400
Subject: [PATCH 08/12] Updating branch

---
 pymc3/distributions/continuous.py        |  6 +++---
 pymc3/tests/test_distributions.py        | 10 +++++++--
 pymc3/tests/test_distributions_random.py | 26 ++++++++++++------------
 3 files changed, 24 insertions(+), 18 deletions(-)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index 31b8557ee5..4a34cf8d18 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2592,7 +2592,7 @@ class ChiSquare(Gamma):
     @classmethod
     def dist(cls, nu, *args, **kwargs):
         nu = at.as_tensor_variable(floatX(nu))
-        super().__init__(alpha=nu / 2.0, beta=0.5, *args, **kwargs)
+        return super().__init__([nu / 2.0, 0.5], *args, **kwargs)
 
     def logp(value, nu):
         """
@@ -2608,7 +2608,7 @@ def logp(value, nu):
         -------
         TensorVariable
         """
-        return Gamma.logp(value, nu/2, 2)
+        return Gamma.logp(value, nu / 2, 2)
 
     def logcdf(value, nu):
         """
@@ -2625,7 +2625,7 @@ def logcdf(value, nu):
         -------
         TensorVariable
         """
-        return Gamma.logcdf(value, nu/2, 2)
+        return Gamma.logcdf(value, nu / 2, 2)
 
 
 # TODO: Remove this once logpt for multiplication is working!
diff --git a/pymc3/tests/test_distributions.py b/pymc3/tests/test_distributions.py
index 062663b1da..e7f7bed408 100644
--- a/pymc3/tests/test_distributions.py
+++ b/pymc3/tests/test_distributions.py
@@ -1030,13 +1030,19 @@ def test_half_normal(self):
             lambda value, sigma: sp.halfnorm.logcdf(value, scale=sigma),
         )
 
-    def test_chi_squared(self):
+    def test_chisquare(self):
         self.check_logp(
             ChiSquare,
             Rplus,
-            {"nu": Rplusdunif},
+            {"nu": Rplus},
             lambda value, nu: sp.chi2.logpdf(value, df=nu),
         )
+        self.check_logcdf(
+            ChiSquare,
+            Rplus,
+            {"nu": Rplus},
+            lambda value, nu: sp.chi2.logcdf(value, df=nu),
+        )
 
     @pytest.mark.xfail(reason="Distribution not refactored yet")
     def test_wald_logp(self):
diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index 2c44f44a53..02ce2c51c5 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -277,19 +277,6 @@ class TestAsymmetricLaplace(BaseTestCases.BaseTestCase):
     params = {"kappa": 1.0, "b": 1.0, "mu": 0.0}
 
 
-class TestChiSquare(BaseTestCases.BaseTestCase):
-    distribution = pm.ChiSquare
-    params = {"nu": 2.0}
-    expected_rv_op_params = {"nu": 2.0}
-    reference_dist_params = {"df": 2.0}
-    reference_dist = seeded_numpy_distribution_builder("chisquare")
-    tests_to_run = [
-        "check_pymc_params_match_rv_op",
-        "check_pymc_draws_match_reference",
-        "check_rv_size",
-    ]
-
-
 @pytest.mark.xfail(reason="This distribution has not been refactored for v4")
 class TestExGaussian(BaseTestCases.BaseTestCase):
     distribution = pm.ExGaussian
@@ -760,6 +747,19 @@ class TestInverseGammaMuSigma(BaseTestDistribution):
     tests_to_run = ["check_pymc_params_match_rv_op"]
 
 
+class TestChiSquare(BaseTestDistribution):
+    pymc_dist = pm.ChiSquare
+    pymc_dist_params = {"nu": 2.0}
+    expected_rv_op_params = {"nu": 2.0}
+    reference_dist_params = {"df": 2.0}
+    reference_dist = seeded_numpy_distribution_builder("chisquare")
+    tests_to_run = [
+        "check_pymc_params_match_rv_op",
+        "check_pymc_draws_match_reference",
+        "check_rv_size",
+    ]
+
+
 class TestBinomial(BaseTestDistribution):
     pymc_dist = pm.Binomial
     pymc_dist_params = {"n": 100, "p": 0.33}

From f3c0144f3b76d03b1b1d8e9d0bac4ccabfe68e1b Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Fri, 4 Jun 2021 15:55:14 -0400
Subject: [PATCH 09/12] Refactoring ChiSquared: bug fixed, tests work locally

---
 docs/source/api/distributions/continuous.rst |  2 +-
 pymc3/distributions/__init__.py              |  4 ++--
 pymc3/distributions/continuous.py            | 10 +++++-----
 pymc3/distributions/multivariate.py          |  4 ++--
 pymc3/gp/gp.py                               |  2 +-
 pymc3/tests/test_distributions.py            |  9 +++++----
 pymc3/tests/test_distributions_random.py     |  4 ++--
 7 files changed, 18 insertions(+), 17 deletions(-)

diff --git a/docs/source/api/distributions/continuous.rst b/docs/source/api/distributions/continuous.rst
index 3399ccf039..9222dcb797 100644
--- a/docs/source/api/distributions/continuous.rst
+++ b/docs/source/api/distributions/continuous.rst
@@ -25,7 +25,7 @@ Continuous
    InverseGamma
    Weibull
    Lognormal
-   ChiSquare
+   ChiSquared
    Wald
    Pareto
    ExGaussian
diff --git a/pymc3/distributions/__init__.py b/pymc3/distributions/__init__.py
index ee51a8d351..807b483712 100644
--- a/pymc3/distributions/__init__.py
+++ b/pymc3/distributions/__init__.py
@@ -27,7 +27,7 @@
     AsymmetricLaplace,
     Beta,
     Cauchy,
-    ChiSquare,
+    ChiSquared,
     ExGaussian,
     Exponential,
     Flat,
@@ -125,7 +125,7 @@
     "Bound",
     "Lognormal",
     "HalfStudentT",
-    "ChiSquare",
+    "ChiSquared",
     "HalfNormal",
     "Wald",
     "Pareto",
diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index 4a34cf8d18..ac57b7d471 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -88,7 +88,7 @@
     "Weibull",
     "HalfStudentT",
     "Lognormal",
-    "ChiSquare",
+    "ChiSquared",
     "HalfNormal",
     "Wald",
     "Pareto",
@@ -2549,7 +2549,7 @@ def logcdf(value, alpha, beta):
         )
 
 
-class ChiSquare(Gamma):
+class ChiSquared(PositiveContinuous):
     r"""
     :math:`\chi^2` log-likelihood.
 
@@ -2592,11 +2592,11 @@ class ChiSquare(Gamma):
     @classmethod
     def dist(cls, nu, *args, **kwargs):
         nu = at.as_tensor_variable(floatX(nu))
-        return super().__init__([nu / 2.0, 0.5], *args, **kwargs)
+        return super().dist([nu], *args, **kwargs)
 
     def logp(value, nu):
         """
-        Calculate log-probability of ChiSquare distribution at specified value.
+        Calculate log-probability of ChiSquared distribution at specified value.
 
         Parameters
         ----------
@@ -2612,7 +2612,7 @@ def logp(value, nu):
 
     def logcdf(value, nu):
         """
-        Compute the log of the cumulative distribution function for ChiSquare distribution
+        Compute the log of the cumulative distribution function for ChiSquared distribution
         at the specified value.
 
         Parameters
diff --git a/pymc3/distributions/multivariate.py b/pymc3/distributions/multivariate.py
index 3bdce21e45..4eb6b01817 100644
--- a/pymc3/distributions/multivariate.py
+++ b/pymc3/distributions/multivariate.py
@@ -40,7 +40,7 @@
 
 from pymc3.aesaraf import floatX, intX
 from pymc3.distributions import transforms
-from pymc3.distributions.continuous import ChiSquare, Normal
+from pymc3.distributions.continuous import ChiSquared, Normal
 from pymc3.distributions.dist_math import bound, factln, logpow
 from pymc3.distributions.distribution import Continuous, Discrete
 from pymc3.distributions.special import gammaln, multigammaln
@@ -905,7 +905,7 @@ def WishartBartlett(name, S, nu, is_cholesky=False, return_cholesky=False, testv
         tril_testval = None
 
     c = at.sqrt(
-        ChiSquare("%s_c" % name, nu - np.arange(2, 2 + n_diag), shape=n_diag, testval=diag_testval)
+        ChiSquared("%s_c" % name, nu - np.arange(2, 2 + n_diag), shape=n_diag, testval=diag_testval)
     )
     pm._log.info("Added new variable %s_c to model diagonal of Wishart." % name)
     z = Normal("%s_z" % name, 0.0, 1.0, shape=n_tril, testval=tril_testval)
diff --git a/pymc3/gp/gp.py b/pymc3/gp/gp.py
index 31fbb41fe3..17e232f0c2 100644
--- a/pymc3/gp/gp.py
+++ b/pymc3/gp/gp.py
@@ -278,7 +278,7 @@ def _build_prior(self, name, X, reparameterize=True, **kwargs):
         cov = stabilize(self.cov_func(X))
         shape = infer_shape(X, kwargs.pop("shape", None))
         if reparameterize:
-            chi2 = pm.ChiSquare(name + "_chi2_", self.nu)
+            chi2 = pm.ChiSquared(name + "_chi2_", self.nu)
             v = pm.Normal(name + "_rotated_", mu=0.0, sigma=1.0, size=shape, **kwargs)
             f = pm.Deterministic(name, (at.sqrt(self.nu) / chi2) * (mu + cholesky(cov).dot(v)))
         else:
diff --git a/pymc3/tests/test_distributions.py b/pymc3/tests/test_distributions.py
index e7f7bed408..0e62ae2894 100644
--- a/pymc3/tests/test_distributions.py
+++ b/pymc3/tests/test_distributions.py
@@ -16,6 +16,7 @@
 import sys
 
 import aesara
+aesara.config.floatX = "float32"
 import aesara.tensor as at
 import numpy as np
 import numpy.random as nr
@@ -48,7 +49,7 @@
     Bound,
     Categorical,
     Cauchy,
-    ChiSquare,
+    ChiSquared,
     Constant,
     DensityDist,
     Dirichlet,
@@ -1030,15 +1031,15 @@ def test_half_normal(self):
             lambda value, sigma: sp.halfnorm.logcdf(value, scale=sigma),
         )
 
-    def test_chisquare(self):
+    def test_chisquared(self):
         self.check_logp(
-            ChiSquare,
+            ChiSquared,
             Rplus,
             {"nu": Rplus},
             lambda value, nu: sp.chi2.logpdf(value, df=nu),
         )
         self.check_logcdf(
-            ChiSquare,
+            ChiSquared,
             Rplus,
             {"nu": Rplus},
             lambda value, nu: sp.chi2.logcdf(value, df=nu),
diff --git a/pymc3/tests/test_distributions_random.py b/pymc3/tests/test_distributions_random.py
index 02ce2c51c5..47344c1272 100644
--- a/pymc3/tests/test_distributions_random.py
+++ b/pymc3/tests/test_distributions_random.py
@@ -747,8 +747,8 @@ class TestInverseGammaMuSigma(BaseTestDistribution):
     tests_to_run = ["check_pymc_params_match_rv_op"]
 
 
-class TestChiSquare(BaseTestDistribution):
-    pymc_dist = pm.ChiSquare
+class TestChiSquared(BaseTestDistribution):
+    pymc_dist = pm.ChiSquared
     pymc_dist_params = {"nu": 2.0}
     expected_rv_op_params = {"nu": 2.0}
     reference_dist_params = {"df": 2.0}

From 163d0b0c679a330f946d93a0bdfeb03c00dd8450 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Fri, 4 Jun 2021 16:07:46 -0400
Subject: [PATCH 10/12] Minor fix: removed float32 specification

---
 pymc3/tests/test_distributions.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pymc3/tests/test_distributions.py b/pymc3/tests/test_distributions.py
index 0e62ae2894..d3e4b7eb27 100644
--- a/pymc3/tests/test_distributions.py
+++ b/pymc3/tests/test_distributions.py
@@ -16,7 +16,6 @@
 import sys
 
 import aesara
-aesara.config.floatX = "float32"
 import aesara.tensor as at
 import numpy as np
 import numpy.random as nr

From b18336ad7dd24937ee0147ff1b17f7a58ab2748a Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Mon, 7 Jun 2021 10:50:00 -0400
Subject: [PATCH 11/12] :sunny: underflow to -inf seems normal in float32

---
 pymc3/tests/test_distributions.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/pymc3/tests/test_distributions.py b/pymc3/tests/test_distributions.py
index d3e4b7eb27..81b780a18e 100644
--- a/pymc3/tests/test_distributions.py
+++ b/pymc3/tests/test_distributions.py
@@ -1030,13 +1030,19 @@ def test_half_normal(self):
             lambda value, sigma: sp.halfnorm.logcdf(value, scale=sigma),
         )
 
-    def test_chisquared(self):
+    def test_chisquared_logp(self):
         self.check_logp(
             ChiSquared,
             Rplus,
             {"nu": Rplus},
             lambda value, nu: sp.chi2.logpdf(value, df=nu),
         )
+
+    @pytest.mark.xfail(
+        condition=(aesara.config.floatX == "float32"),
+        reason="Fails on float32 due to numerical issues",
+    )
+    def test_chisquared_logcdf(self):
         self.check_logcdf(
             ChiSquared,
             Rplus,

From 074b3af86a521ddb1131464ce6391e2a680452b7 Mon Sep 17 00:00:00 2001
From: Larry Dong <larry.dong@mail.mcgill.ca>
Date: Mon, 7 Jun 2021 10:53:23 -0400
Subject: [PATCH 12/12] Minor fix in documentation

---
 pymc3/distributions/continuous.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pymc3/distributions/continuous.py b/pymc3/distributions/continuous.py
index ac57b7d471..cd2244b39e 100644
--- a/pymc3/distributions/continuous.py
+++ b/pymc3/distributions/continuous.py
@@ -2584,7 +2584,7 @@ class ChiSquared(PositiveContinuous):
 
     Parameters
     ----------
-    nu: int
+    nu: float
         Degrees of freedom (nu > 0).
     """
     rv_op = chisquare