diff --git a/.mypyignore-todo b/.mypyignore-todo
index 6150cb02..cf72c506 100644
--- a/.mypyignore-todo
+++ b/.mypyignore-todo
@@ -1,4 +1,4 @@
 scipy\.stats\.__all__
 scipy\.stats\.(Normal|Uniform)
-scipy\.stats\.(_distribution_infrastructure\.)?(abs|exp|make_distribution|order_statistic)
+scipy\.stats\.(_distribution_infrastructure\.)?(make_distribution|order_statistic)
 scipy\.stats\._distribution_infrastructure\.(Folded|OrderStatistic)Distribution\.__init__
diff --git a/scipy-stubs/stats/__init__.pyi b/scipy-stubs/stats/__init__.pyi
index a69f8aa7..ef0b0e18 100644
--- a/scipy-stubs/stats/__init__.pyi
+++ b/scipy-stubs/stats/__init__.pyi
@@ -7,7 +7,7 @@ from ._correlation import chatterjeexi
 from ._covariance import Covariance
 
 # TODO(jorenham)
-from ._distribution_infrastructure import Mixture, exp, log, truncate  # abs, make_distribution, order_statistic
+from ._distribution_infrastructure import Mixture, abs, exp, log, truncate  # make_distribution, order_statistic
 from ._entropy import differential_entropy, entropy
 from ._fit import fit, goodness_of_fit
 from ._hypotests import (
@@ -314,7 +314,7 @@ __all__ = [
     # "Normal",
     "PermutationMethod",
     # "Uniform",
-    # "abs",
+    "abs",
     "alexandergovern",
     "alpha",
     "anderson",
diff --git a/scipy-stubs/stats/_distribution_infrastructure.pyi b/scipy-stubs/stats/_distribution_infrastructure.pyi
index 6d279b84..ad92e599 100644
--- a/scipy-stubs/stats/_distribution_infrastructure.pyi
+++ b/scipy-stubs/stats/_distribution_infrastructure.pyi
@@ -438,8 +438,56 @@ class FoldedDistribution(
     TransformedDistribution[_CDistT_co, _FloatingT_co, _ShapeT0_co],
     Generic[_CDistT_co, _FloatingT_co, _ShapeT0_co],
 ):
-    # TODO(jorenham)
-    ...
+    @overload
+    def __init__(
+        self: FoldedDistribution[_CDistT0, np.floating[Any], tuple[()]],
+        X: _CDistT0,
+        /,
+        *args: Never,
+        tol: opt.Just[float] | _Null = ...,
+        validation_policy: _ValidationPolicy = None,
+        cache_policy: _CachePolicy = None,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: FoldedDistribution[_CDistT1, np.floating[Any], tuple[int]],
+        X: _CDistT1,
+        /,
+        *args: Never,
+        tol: opt.Just[float] | _Null = ...,
+        validation_policy: _ValidationPolicy = None,
+        cache_policy: _CachePolicy = None,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: FoldedDistribution[_CDistT2, np.floating[Any], tuple[int, int]],
+        X: _CDistT2,
+        /,
+        *args: Never,
+        tol: opt.Just[float] | _Null = ...,
+        validation_policy: _ValidationPolicy = None,
+        cache_policy: _CachePolicy = None,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: FoldedDistribution[_CDistT3, np.floating[Any], tuple[int, int, int]],
+        X: _CDistT3,
+        /,
+        *args: Never,
+        tol: opt.Just[float] | _Null = ...,
+        validation_policy: _ValidationPolicy = None,
+        cache_policy: _CachePolicy = None,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: FoldedDistribution[_CDistT, np.floating[Any], tuple[int, ...]],
+        X: _CDistT,
+        /,
+        *args: Never,
+        tol: opt.Just[float] | _Null = ...,
+        validation_policy: _ValidationPolicy = None,
+        cache_policy: _CachePolicy = None,
+    ) -> None: ...
 
 class TruncatedDistribution(
     TransformedDistribution[_CDistT_co, _FloatingT_co, _ShapeT0_co],
@@ -515,10 +563,6 @@ class TruncatedDistribution(
         cache_policy: _CachePolicy = None,
     ) -> None: ...
 
-class OrderStatisticDistribution(TransformedDistribution[_CDistT_co, np.float64, _ShapeT0_co], Generic[_CDistT_co, _ShapeT0_co]):
-    # TODO(jorenham)
-    ...
-
 # without HKT there's no reasonable way tot determine the floating scalar type
 class MonotonicTransformedDistribution(
     TransformedDistribution[_CDistT_co, np.floating[Any], _ShapeT0_co],
@@ -547,6 +591,10 @@ class MonotonicTransformedDistribution(
         cache_policy: _CachePolicy = None,
     ) -> None: ...
 
+class OrderStatisticDistribution(TransformedDistribution[_CDistT_co, np.float64, _ShapeT0_co], Generic[_CDistT_co, _ShapeT0_co]):
+    # TODO(jorenham)
+    ...
+
 class Mixture(_BaseDistribution[_FloatingT_co, tuple[()]], Generic[_FloatingT_co]):
     _shape: tuple[()]
     _dtype: np.dtype[_FloatingT_co]
@@ -600,6 +648,18 @@ def truncate(
     ub: onp.ToFloat | onp.ToFloatND = ...,
 ) -> TruncatedDistribution[_CDistT, np.floating[Any], tuple[int, ...]]: ...
 
+#
+@overload
+def abs(X: _CDistT0, /) -> FoldedDistribution[_CDistT0, np.floating[Any], tuple[()]]: ...
+@overload
+def abs(X: _CDistT1, /) -> FoldedDistribution[_CDistT1, np.floating[Any], tuple[int]]: ...
+@overload
+def abs(X: _CDistT2, /) -> FoldedDistribution[_CDistT2, np.floating[Any], tuple[int, int]]: ...
+@overload
+def abs(X: _CDistT3, /) -> FoldedDistribution[_CDistT3, np.floating[Any], tuple[int, int, int]]: ...
+@overload
+def abs(X: _CDistT, /) -> FoldedDistribution[_CDistT, np.floating[Any], tuple[int, ...]]: ...
+
 #
 @overload
 def exp(X: _CDistT0, /) -> MonotonicTransformedDistribution[_CDistT0, tuple[()]]: ...