Merge docs/vocabulary (#75)

src/history.rs

@@ -72,7 +72,22 @@ impl<T: Time, D: Drift<T>, O: Observer<T>, K: Eq + Hash + Clone> HistoryBuilder<
         self
     }
 
-    /// Prior standard deviation.
+    /// Prior standard deviation: how unsure the model is about a competitor's
+    /// **skill** before it has seen them play.
+    ///
+    /// The first of the two noise knobs, and the one people reach for by
+    /// mistake. `sigma` is *epistemic* — it is what the model does not yet
+    /// know, and evidence shrinks it. [`HistoryBuilder::beta`] is *aleatoric*
+    /// — how much a single showing scatters around the skill, which no amount
+    /// of evidence removes.
+    ///
+    /// So: results move ratings too slowly for your taste → raise `sigma` (or
+    /// `gamma`, if the problem is that skill genuinely moves). A single upset
+    /// swings ratings too far → raise `beta`, because you are telling the model
+    /// that one result is weaker evidence than it assumed.
+    ///
+    /// The default is six betas, deliberately wide: a new competitor's first
+    /// result should move them a long way.
     ///
     /// # Panics
     ///
@@ -91,7 +106,19 @@ impl<T: Time, D: Drift<T>, O: Observer<T>, K: Eq + Hash + Clone> HistoryBuilder<
         self
     }
 
-    /// Per-event performance noise.
+    /// Per-event performance noise: how much a single showing scatters around
+    /// a competitor's **skill**.
+    ///
+    /// The second noise knob, and the one that sets the scale of the whole
+    /// system — [`SIGMA`](crate::SIGMA) and [`GAMMA`](crate::GAMMA) are both
+    /// defined as multiples of it. Unlike
+    /// [`sigma`](HistoryBuilder::sigma), this is *aleatoric*: it is the
+    /// irreducible day-to-day variation, so evidence never shrinks it. It is
+    /// also what makes an upset possible at all — with `beta == 0` the better
+    /// competitor always wins.
+    ///
+    /// Larger `beta` means each result carries less information, so ratings
+    /// move less per game and the draw margin implied by `p_draw` is wider.
     ///
     /// # Panics
     ///
@@ -2685,8 +2712,11 @@ impl<T: Time, D: Drift<T>, O: Observer<T>, K: Eq + Hash + Clone> History<T, D, O
                     kinds.push(EventKind::Ranked);
                     ranks.iter().map(|&r| max_rank - r as f64).collect()
                 }
-                crate::Outcome::Scored { scores, sigma } => {
-                    let resolved = sigma.unwrap_or(self.score_sigma);
+                crate::Outcome::Scored {
+                    scores,
+                    score_sigma,
+                } => {
+                    let resolved = score_sigma.unwrap_or(self.score_sigma);
                     if resolved <= 0.0 || resolved.is_nan() {
                         return Err(InferenceError::InvalidParameter {
                             name: "score_sigma",

src/outcome.rs

@@ -1,6 +1,6 @@
 //! Outcome of a match.
 //!
-//! `Ranked(ranks)` for ordinal results; `Scored { scores, sigma }` for
+//! `Ranked(ranks)` for ordinal results; `Scored { scores, score_sigma }` for
 //! continuous per-team scores (engages `MarginFactor` in the engine).
 
 use smallvec::SmallVec;
@@ -10,7 +10,7 @@ use smallvec::SmallVec;
 /// `Ranked(ranks)`: lower rank = better. Equal ranks mean a tie between those
 /// teams. `ranks.len()` must equal the number of teams in the event.
 ///
-/// `Scored { scores, sigma }`: higher score = better. Adjacent (sorted) pairs
+/// `Scored { scores, score_sigma }`: higher score = better. Adjacent (sorted) pairs
 /// feed observed margins to `MarginFactor`. `scores.len()` must equal the
 /// number of teams in the event. `sigma` overrides `HistoryBuilder::score_sigma`
 /// when `Some`; `None` inherits the history default.
@@ -34,7 +34,8 @@ pub enum Outcome {
     ///
     /// Unlike `Ranked`, the *sizes* of the differences are evidence. Teams are
     /// sorted by score and each adjacent pair's observed gap is fed to a
-    /// `MarginFactor` as a measurement with standard deviation `sigma`, so
+    /// `MarginFactor` as a measurement with standard deviation `score_sigma`,
+    /// so
     /// beating a team by ten says more than beating them by one.
     #[non_exhaustive]
     Scored {
@@ -43,7 +44,7 @@ pub enum Outcome {
         scores: SmallVec<[f64; 4]>,
         /// Per-event noise override. `None` means inherit
         /// `HistoryBuilder::score_sigma`. Must be `> 0.0` if `Some`.
-        sigma: Option<f64>,
+        score_sigma: Option<f64>,
     },
 }
 
@@ -106,20 +107,20 @@ impl Outcome {
     pub fn scores<I: IntoIterator<Item = f64>>(scores: I) -> Self {
         Self::Scored {
             scores: scores.into_iter().collect(),
-            sigma: None,
+            score_sigma: None,
         }
     }
 
     /// Explicit per-team continuous scores with a per-event noise override.
     ///
-    /// `sigma` must be `> 0.0`. Constructing an `Outcome` with a non-positive
-    /// or NaN sigma is allowed; the value is rejected with
+    /// `score_sigma` must be `> 0.0`. Constructing an `Outcome` with a
+    /// non-positive or NaN value is allowed; the value is rejected with
     /// `InferenceError::InvalidParameter` when the event is ingested, so
     /// callers get an error rather than a panic.
-    pub fn scores_with_sigma<I: IntoIterator<Item = f64>>(scores: I, sigma: f64) -> Self {
+    pub fn scores_with_sigma<I: IntoIterator<Item = f64>>(scores: I, score_sigma: f64) -> Self {
         Self::Scored {
             scores: scores.into_iter().collect(),
-            sigma: Some(sigma),
+            score_sigma: Some(score_sigma),
         }
     }
 
@@ -219,7 +220,7 @@ mod tests {
     fn scores_constructor_leaves_sigma_unset() {
         let o = Outcome::scores([3.0, 1.0]);
         match o {
-            Outcome::Scored { scores: _, sigma } => assert!(sigma.is_none()),
+            Outcome::Scored { score_sigma, .. } => assert!(score_sigma.is_none()),
             Outcome::Ranked(_) => panic!("expected Scored variant"),
         }
     }
@@ -228,7 +229,7 @@ mod tests {
     fn scores_with_sigma_sets_sigma_some() {
         let o = Outcome::scores_with_sigma([3.0, 1.0], 2.0);
         match o {
-            Outcome::Scored { scores: _, sigma } => assert_eq!(sigma, Some(2.0)),
+            Outcome::Scored { score_sigma, .. } => assert_eq!(score_sigma, Some(2.0)),
             Outcome::Ranked(_) => panic!("expected Scored variant"),
         }
     }
@@ -240,7 +241,7 @@ mod tests {
     fn scores_with_sigma_defers_validation_to_ingestion() {
         let o = Outcome::scores_with_sigma([3.0, 1.0], 0.0);
         match o {
-            Outcome::Scored { sigma, .. } => assert_eq!(sigma, Some(0.0)),
+            Outcome::Scored { score_sigma, .. } => assert_eq!(score_sigma, Some(0.0)),
             Outcome::Ranked(_) => panic!("expected Scored variant"),
         }
     }