Add Markov regime-switching models

[mortentabor]

Summary

• New markov/ subpackage with MarkovRegression, MarkovAR, and MarkovADL wrapping statsmodels' Markov switching implementation
• Restricted transition matrices (RestrictedMarkovRegression/AR) for enforcing exact zeros — enables Chib (1998) non-recurring (structural break) structure
• Sequential restriction testing — novel GETS-style algorithm that tests and imposes individual transition probability restrictions with Holm-Bonferroni correction
• NonRecurringRegimeTest — LR test for non-recurring vs unrestricted transitions with chi-bar-squared and bootstrap critical values
• RegimeNumberSelection — select K via AIC/BIC/HQIC or sequential LRT
• 5 visualization functions: smoothed probabilities, regime shading, transition matrix heatmap, parameter time series, IC comparison plot
• Convenience methods markov_switching() on OLS, AR, and ADL for one-way mapping to MS models
• 98 new tests across 7 test files (816 total, all passing)

Architecture

src/regimes/markov/
    __init__.py                     # Re-exports 15 public classes
    models.py                       # MarkovRegression, MarkovAR, MarkovADL
    results.py                      # MarkovSwitchingResultsBase + concrete results
    restricted.py                   # Constrained transition matrices
    sequential_restriction.py       # NonRecurringRegimeTest, SequentialRestrictionTest
    selection.py                    # RegimeNumberSelection

No overlap with PR #4 (Bai-Perron fixes) — these can merge in either order.

Test plan

• 98 new Markov tests pass (tests/test_markov/, tests/test_visualization/test_markov_viz.py)
• All 718 existing tests still pass (no regressions)
• Smoke tested: MarkovRegression, MarkovAR, MarkovADL fit and results
• Smoke tested: RestrictedMarkovRegression with restrictions enforced
• Smoke tested: RegimeNumberSelection correctly selects K=2 on 2-regime data
• All visualization functions produce valid Figure/Axes
• All imports work from top-level import regimes as rg

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