feat: add filtered learning curves

learning_curve returns post-convergence posteriors, so every point is
smoothed: the estimate at a given date incorporates rounds played years
later. On ustat's data that starts six players' curves already spread apart
at sigma 0.9-1.6 against a prior of 6.0, barely moving thereafter.

filtered_learning_curve plots the same competitor on forward-only
information, so everyone starts at the prior and fans out. It could not be
reconstructed from the public API before: a caller could only refit over
events[0..k] for every k, which is O(n^2) fits for something one forward
pass already computes.

tests/filtered.rs

@@ -50,3 +50,68 @@ fn filtered_evidence_sits_between_coin_flip_and_batch() {
          scores each game on strictly less information than smoothing does"
     );
 }
+
+#[test]
+fn filtered_first_point_is_less_certain_than_smoothed() {
+    let mut history = repeated_winner(12);
+
+    history.converge().unwrap();
+
+    let smoothed = history.learning_curve("a");
+    let filtered = history.filtered_learning_curve("a");
+
+    assert_eq!(
+        smoothed.len(),
+        filtered.len(),
+        "both curves must cover the same time points"
+    );
+
+    let (smoothed_time, first_smoothed) = smoothed[0];
+    let (filtered_time, first_filtered) = filtered[0];
+
+    assert_eq!(smoothed_time, filtered_time);
+
+    assert!(
+        first_filtered.sigma() > first_smoothed.sigma(),
+        "filtered sigma {} at the first point is not above smoothed {}; the smoother \
+         collapses uncertainty before the first round is drawn, which is the whole \
+         reason this method exists",
+        first_filtered.sigma(),
+        first_smoothed.sigma()
+    );
+
+    assert!(
+        first_filtered.sigma() < trueskill_tt::SIGMA,
+        "filtered sigma {} at the first point is not below the prior {}; one game was \
+         played, so some uncertainty must have been resolved",
+        first_filtered.sigma(),
+        trueskill_tt::SIGMA
+    );
+
+    for pair in filtered.windows(2) {
+        assert!(
+            pair[1].1.mu() > pair[0].1.mu(),
+            "filtered mu must climb at every step for a competitor who wins every \
+             game: t={} mu={} then t={} mu={}",
+            pair[0].0,
+            pair[0].1.mu(),
+            pair[1].0,
+            pair[1].1.mu()
+        );
+    }
+}
+
+#[test]
+fn filtered_curves_plural_agrees_with_singular() {
+    let mut history = repeated_winner(4);
+
+    history.converge().unwrap();
+
+    let curves = history.filtered_learning_curves();
+
+    assert_eq!(
+        curves["b"],
+        history.filtered_learning_curve("b"),
+        "the plural form must agree with the singular for the same key"
+    );
+}