some new features

.venv/lib/python3.12/site-packages/statsmodels/compat/scipy.py

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+from packaging.version import Version, parse
+
+import numpy as np
+import scipy
+
+SP_VERSION = parse(scipy.__version__)
+SP_LT_15 = SP_VERSION < Version("1.4.99")
+SCIPY_GT_14 = not SP_LT_15
+SP_LT_16 = SP_VERSION < Version("1.5.99")
+SP_LT_17 = SP_VERSION < Version("1.6.99")
+SP_LT_19 = SP_VERSION < Version("1.8.99")
+
+
+def _next_regular(target):
+    """
+    Find the next regular number greater than or equal to target.
+    Regular numbers are composites of the prime factors 2, 3, and 5.
+    Also known as 5-smooth numbers or Hamming numbers, these are the optimal
+    size for inputs to FFTPACK.
+
+    Target must be a positive integer.
+    """
+    if target <= 6:
+        return target
+
+    # Quickly check if it's already a power of 2
+    if not (target & (target - 1)):
+        return target
+
+    match = float("inf")  # Anything found will be smaller
+    p5 = 1
+    while p5 < target:
+        p35 = p5
+        while p35 < target:
+            # Ceiling integer division, avoiding conversion to float
+            # (quotient = ceil(target / p35))
+            quotient = -(-target // p35)
+            # Quickly find next power of 2 >= quotient
+            p2 = 2 ** ((quotient - 1).bit_length())
+
+            N = p2 * p35
+            if N == target:
+                return N
+            elif N < match:
+                match = N
+            p35 *= 3
+            if p35 == target:
+                return p35
+        if p35 < match:
+            match = p35
+        p5 *= 5
+        if p5 == target:
+            return p5
+    if p5 < match:
+        match = p5
+    return match
+
+
+def _valarray(shape, value=np.nan, typecode=None):
+    """Return an array of all value."""
+
+    out = np.ones(shape, dtype=bool) * value
+    if typecode is not None:
+        out = out.astype(typecode)
+    if not isinstance(out, np.ndarray):
+        out = np.asarray(out)
+    return out
+
+
+if SP_LT_16:
+    # copied from scipy, added to scipy in 1.6.0
+    from ._scipy_multivariate_t import multivariate_t  # noqa: F401
+else:
+    from scipy.stats import multivariate_t  # noqa: F401