Add weighted versions of the Gaussian kernel score (#77)

* fix lint issues in gaussian kernel score

* fix lint issues in gaussian kernel score test

* fix lint issues in gaussian kernel score test

* fix lint issues in multivariate gaussian kernel score test

* add threshold-weighted univariate gaussian kernel score

* add threshold-weighted univariate gaussian kernel score

* add tests for threshold weighted univariate gaussian kernel score

* add outcome-weighted gaussian kernel scores

* add multivariate threshold weighted gaussian kernel score

* re-add univariate weighted gaussian kernel scores

* re-add univariate weighted gaussian kernel scores

* fix bug in weighted gaussian kernel scores for torch backend

* fix bug in weighted multivariate gaussian kernel scores

* fix bug in weighted multivariate gaussian kernel scores

docs/api/kernels.md

@@ -1,3 +1,17 @@
 # Kernel scores
 
-::: scoringrules.gks_ensemble
+::: scoringrules.gksuv_ensemble
+
+::: scoringrules.twgksuv_ensemble
+
+::: scoringrules.owgksuv_ensemble
+
+::: scoringrules.vrgksuv_ensemble
+
+::: scoringrules.gksmv_ensemble
+
+::: scoringrules.twgksmv_ensemble
+
+::: scoringrules.owgksmv_ensemble
+
+::: scoringrules.vrgksmv_ensemble

scoringrules/__init__.py

@@ -85,7 +85,13 @@
 )
 from scoringrules._kernels import (
     gksuv_ensemble,
+    twgksuv_ensemble,
+    owgksuv_ensemble,
+    vrgksuv_ensemble,
     gksmv_ensemble,
+    twgksmv_ensemble,
+    owgksmv_ensemble,
+    vrgksmv_ensemble,
 )
 
 from scoringrules.backend import backends, register_backend
@@ -159,8 +165,6 @@
     "rps_score",
     "log_score",
     "rls_score",
-    "gksuv_ensemble",
-    "gksmv_ensemble",
     "error_spread_score",
     "energy_score",
     "owenergy_score",
@@ -170,6 +174,14 @@
     "owvariogram_score",
     "twvariogram_score",
     "vrvariogram_score",
+    "gksuv_ensemble",
+    "twgksuv_ensemble",
+    "owgksuv_ensemble",
+    "vrgksuv_ensemble",
+    "gksmv_ensemble",
+    "twgksmv_ensemble",
+    "owgksmv_ensemble",
+    "vrgksmv_ensemble",
     "interval_score",
     "weighted_interval_score",
 ]

scoringrules/_energy.py

@@ -185,7 +185,7 @@ def vrenergy_score(
 ) -> "Array":
     r"""Compute the Vertically Re-scaled Energy Score (vrES) for a finite multivariate ensemble.
 
-    Computation is performed using the ensemble representation of the twES in
+    Computation is performed using the ensemble representation of the vrES in
     [Allen et al. (2022)](https://arxiv.org/abs/2202.12732):
 
     \[
@@ -196,7 +196,7 @@ def vrenergy_score(
     \]
 
     where $F_{ens}$ is the ensemble forecast $\mathbf{x}_{1}, \dots, \mathbf{x}_{M}$ with
-    $M$ members, and $v$ is the chaining function used to target particular outcomes.
+    $M$ members, and $w$ is the weight function used to target particular outcomes.
 
 
     Parameters