update documentation link and prepare release tag

Author: frazane

README.md

@@ -45,7 +45,7 @@ pip install scoringrules
 
 ## Documentation
 
-Learn more about `scoringrules` in its official documentation at https://frazane.github.io/scoringrules/.
+Learn more about `scoringrules` in its official documentation at https://scoringrules.readthedocs.io/en/latest/.
 
 
 ## Quick example
@@ -77,5 +77,3 @@ grateful for fruitful discussions with the authors.
 - The quality of this library has also benefited a lot from discussions with (and contributions from)
 Nick Loveday and Tennessee Leeuwenburg, whose python library [`scores`](https://github.com/nci/scores)
 similarly provides a comprehensive collection of forecast evaluation methods.
-- The implementation of the ensemble-based metrics as jit-compiled numpy generalized `ufuncs`
-was first proposed in [`properscoring`](https://github.com/properscoring/properscoring), released under Apache License, Version 2.0.

docs/index.md

@@ -65,7 +65,7 @@ pip install scoringrules
 
 ## Documentation
 
-Learn more about `scoringrules` in its official documentation at https://frazane.github.io/scoringrules/.
+Learn more about `scoringrules` in its official documentation at https://scoringrules.readthedocs.io/en/latest/.
 
 
 ## Quick example
@@ -97,5 +97,3 @@ grateful for fruitful discussions with the authors.
 - The quality of this library has also benefited a lot from discussions with (and contributions from)
 Nick Loveday and Tennessee Leeuwenburg, whose python library [`scores`](https://github.com/nci/scores)
 similarly provides a comprehensive collection of forecast evaluation methods.
-- The implementation of the ensemble-based metrics as jit-compiled numpy generalized `ufuncs`
-was first proposed in [`properscoring`](https://github.com/properscoring/properscoring), released under Apache License, Version 2.0.

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "scoringrules"
-version = "0.7.1"
+version = "0.8.0"
 description = "Scoring rules for probabilistic forecast evaluation."
 readme = "README.md"
 requires-python = ">=3.10"