Each probability distribution is defined in a module for that distribution. For example, the normal distribution is defined in Probability.Distribution.Normal
, which is located at haskell/Probability/Distribution/Normal.hs.
To make a new distribution mydist
, you should follow these steps, using the normal distribution as a template:
Probability.Distribution.MyDist
in haskell/Probability/Distribution/Mydist.hs
using Normal.hs
as a template.builtin_function_mydist_density
in src/builtins/Distribution.cc
using builtin_function_normal_density
as a template.builtin_function_sample_mydist
in src/builtins/Distribution.cc
using builtin_function_sample_normal
as a template.builtin_function_mydist_quantile
in src/builtins/Distribution.cc
using builtin_function_normal_quantile
as a template.bindings/distributions/mydist.json
using bindings/distribution/normal.json
as a template.For a distribution, you need to add a function that constructs a Distribution object.
For example, the Normal distribution is defined as:
builtin normal_density 3 "normal_density" "Distribution"
builtin normal_quantile 3 "normal_quantile" "Distribution"
builtin builtin_sample_normal 3 "sample_normal" "Distribution"
sample_normal m s = RandomStructure do_nothing modifiable_structure $ liftIO (IOAction (\state -> (state, builtin_sample_normal m s state)))
normal m s = Distribution (\x -> [normal_density m s x]) (normal_quantile m s) (sample_normal m s) realLine
The first argument to Distribution
is a function that returns a list of terms which yield the density when multiplied together. In this case there is just one term.
A normal_density
function takes an extra argument after the distribution parameters. For example, the normal density takes 3 arguments, so that (normal_density m s)
is a function of the third argument.
A quantile function takes an extra argument after the distribution parameters. For example, the normal quantile takes 3 arguments, so that (normal_quantile m s)
is a function of the third argument. The extra argument should have type double
, and ranges from 0 to 1.
If the function is not univariate, or does not have a quantile functon, set the quantile function to (no_quantile "distribution name")
. This will later change to use polymorphism, where only 1-dimensional functions will have a quantile attribute.
To construct a random sample from a C++ procedure, access the n
th parameter via Args.evaluate_(n)
(with an underscore) instead of Args.evaluate(n)
. For example:
extern "C" closure builtin_function_sample_normal(OperationArgs& Args)
{
double a1 = Args.evaluate_(0).as_double();
double a2 = Args.evaluate_(1).as_double();
Args.make_changeable();
return { gaussian(a1, a2) };
}
A density function should return type log_double_t
.