commit 5c73980d70ad6607b3756f2ce90d48cbd5d30314
parent 507a2b6237f8ef417e12668816b5feec24286675
Author: Marco Zocca <marco.zocca@recordunion.com>
Date: Wed, 9 May 2018 14:28:51 +0200
update readme
Diffstat:
| M | README.md | | | 43 | +++++++++++++++++++++++++++++++++++++++---- |
1 file changed, 39 insertions(+), 4 deletions(-)
diff --git a/README.md b/README.md
@@ -13,21 +13,22 @@ This implementation is a thin layer over `mwc-random`, which handles RNG
state-passing automatically by using a `PrimMonad` like `IO` or `ST s` under
the hood.
+
Examples
--------
-Transform a distribution's support while leaving its density structure
+1. Transform a distribution's support while leaving its density structure
invariant:
- -- uniform over [0, 1] to uniform over [1, 2]
+ -- uniform over [0, 1] transformed to uniform over [1, 2]
succ <$> uniform
-Sequence distributions together using bind:
+2. Sequence distributions together using bind:
-- a beta-binomial composite distribution
beta 1 10 >>= binomial 10
-Use do-notation to build complex joint distributions from composable,
+3. Use do-notation to build complex joint distributions from composable,
local conditionals:
hierarchicalModel = do
@@ -38,3 +39,36 @@ local conditionals:
n <- uniformR (5, 10)
binomial n p
+
+
+Included probability distributions
+-------------
+
+## Continuous
+
+* Uniform
+* Normal
+* Log-Normal
+* Exponential
+* Inverse Gaussian
+* Laplace
+* Gamma
+* Inverse Gamma
+* Weibull
+* Chi-squared
+* Beta
+* Student t
+* Pareto
+* Dirichlet process
+* Symmetric Dirichlet process
+
+## Discrete
+
+* Discrete uniform
+* Zipf-Mandelbrot
+* Categorical
+* Bernoulli
+* Binomial
+* Negative Binomial
+* Multinomial
+* Poisson
+\ No newline at end of file
