Fix catastrophic cancellation error in poisson logpdf when k and mu are large

[rahulb0802]

This replaces the current direct-formula method in logpdf with Loader's (2000) saddle-point approx, ported from a change I've been working on in SciPy's scipy.stats.poisson.logpmf. The current formula loses precision due to cancellation when k is close to mu and both are large. The new form implemented avoids this.

Two new helpers are added to poisson_detail:

• stirlerr(n): Stirling's series remainder. Direct path for small n, asymptotic series for large n
• bd0(mean, k): Deviance term. Direct path and series expansion for |v| < 0.1 to avoid cancellation when k and mu are close

All existing poisson tests pass (across all real types). I also added accuracy checks for other values, validated against mpmath (1000-digit) reference values, including large-magnitude cases. No regressions as per CI checks.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 95.40%. Comparing base (64a8d75) to head (487009b).

Additional details and impacted files

@@           Coverage Diff            @@
##           develop    #1438   +/-   ##
========================================
  Coverage    95.39%   95.40%           
========================================
  Files          829      829           
  Lines        69186    69219   +33     
========================================
+ Hits         66003    66039   +36     
+ Misses        3183     3180    -3     

Files with missing lines	Coverage Δ
include/boost/math/distributions/poisson.hpp	86.03% <100.00%> (+2.16%)	⬆️
test/test_poisson.cpp	99.19% <100.00%> (+0.06%)	⬆️

... and 1 file with indirect coverage changes

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