Fix VEI crash on degenerate market proxy (qcut 'Bin edges must be unique')

[ABtheMD]

Problem

get_vertical_equity_scores (openavmkit/vertical_equity_study.py) raises
ValueError: Bin edges must be unique and aborts the entire modeling run
whenever the VEI "market proxy" is degenerate but the sample has ≥ 20 rows (so
the existing small-sample guard doesn't apply). Two real triggers:

1. Valuation all-zero / all-NaN. Hit in practice on a tax-exempt model
   group, whose assessed values are $0. Then median_ratio == 0, so
   market_proxy = sale*0.5 + valuation/median_ratio = sale*0.5 + 0/0 = NaN for
   every row, and pd.qcut raises on all-NaN bin edges.
2. Concentrated values. Many identical / capped / round-number amounts
   (common in assessment rolls) put several quantile boundaries on the same
   edge, so pd.qcut(q=N) raises even when there are enough distinct values
   overall.

Either way, one degenerate group takes down a run where every other group
modeled fine.

Fix

Purely defensive — valid inputs are unaffected; degenerate inputs now degrade to
a NaN result (exactly as the function already does for < 20 observations)
instead of raising:

• Return the NaN result dict when median_ratio is 0/non-finite or the
  market proxy has < 2 distinct finite values.
• Pass duplicates="drop" to pd.qcut and index the actual top/bottom
  tiers (group_stats.index.min()/max()) rather than assuming labels
  0..percentile_group_count-1; return NaN if fewer than 2 tiers can be formed.

Tests

Adds tests/test_vertical_equity.py:

• test_all_zero_valuation_returns_nan_not_crash (the tax-exempt repro)
• test_constant_market_proxy_returns_nan_not_crash
• test_concentrated_values_do_not_crash
• test_healthy_data_still_returns_finite_vei (control — happy path unchanged)

All four pass; test_ensemble.py, test_modeling.py, test_horizontal_equity.py
still green (no regression).

Found while running a full all-class county model (Berks County, PA) on v0.6.0.

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[ABtheMD]

recheck

[ABtheMD]

The PR was generated by Claude, so I just wanted to add my own human understanding here. I was working on VEI metrics for each of the land classes, when the library crashed on exempt.

Because the vast majority of the exempts have an assessment of $0, which ultimately gives us a whole lot of NaNs when we are trying to calculate the market_proxy. I suppose there's an alternative path where we exclude Exempts from VEI calculation, but this seems cleaner and more foolproof.