commit ac09f996fac0ca05eedc67f41664f9f5db68891f
parent 60eb2a98f8e01c4a1fd4671a293a7762663dd5be
Author: Jared Tobin <jared@jtobin.io>
Date: Tue, 10 Sep 2019 14:33:42 -0230
readme: fix typo, add dissertation link
Diffstat:
1 file changed, 5 insertions(+), 1 deletion(-)
diff --git a/README.md b/README.md
@@ -15,7 +15,7 @@ provided by a simple `Num` instance enabled by an `Applicative` instance.
Create measures from graphs of other measures using the `Monad` instance and
do-notation.
-Query measures by integrating meaurable functions against them. Extract
+Query measures by integrating measurable functions against them. Extract
moments, cumulative density functions, or probabilities.
You can check out a few blog posts I wrote about the theoretical foundations
@@ -25,10 +25,14 @@ and implementation of the library here:
* [Implementing the Giry Monad][impl]
* [The Applicative Structure of the Giry Monad][appl]
+A more polished and extended version of the above appears in chapter three of
+[my dissertation][diss].
+
Caveat: while fun to play with, and rewarding to see how measures fit together,
measure operations as nested integrals are exponentially complex. Don't expect
them to scale very far!
+[diss]: https://jtobin.io/assets/jtobin-dissertation.pdf
[foun]: https://jtobin.io/giry-monad-foundations
[impl]: https://jtobin.io/giry-monad-implementation
[appl]: https://jtobin.io/giry-monad-applicative
