Re: [boost] [Math/Statistical Distributions] Rethinking of distribution template parameters.

Subject: Re: [boost] [Math/Statistical Distributions] Rethinking of distribution template parameters.
From: Marco Guazzone (marco.guazzone_at_[hidden])
Date: 2009-05-19 09:16:04

On Tue, May 19, 2009 at 2:49 PM, Marco Guazzone
<marco.guazzone_at_[hidden]> wrote:
> Dear Boost developers,
>
> This is a feature request for the next version of Math/Statisical
> Distributions lib.
>
> Currently, due to lack of input type information, discrete
> distributions can only be "emulated" by using the discrete_quantile
> policy.
> However, doing so the effective quantile type is still a real type.
>
> In my opinion, this have at least two disadvantages:
> 1. Operations are slow since the underlying quantile type is still
> real. Instead, operations on really integral types are generally
> faster.
> 2. Quantile comparison might be inaccurate since we are comparing real types
>
> So, for improving the support of discrete distributions, I think it
> would be nice if the all probability distributions gain a third
> template parameter, named, for instance, InputType.

Just for completeness, the different helper functions would become:

--- [code_snip] ---
// Discrete Uniform Distribution

template <typename InputType, typename ValueType, typename Policy>
inline ValueType pdf(const discrete_uniform_distribution<InputType,
ValueType, Policy>& dist, const InputType& x)
{
  return ValueType(1.0)/(dist.upper()-dist.lower()+1);
}

template <typename InputType, typename ValueType, typename Policy>
inline ValueType cdf(const discrete_uniform_distribution<InputType,
ValueType, Policy>& dist, const InputType& q)
{
  if (q <= dist.lower()) return 0;
  if (q >= dist.upper()) return 1;

  return (q-dist.lower()+1)/ValueType(dist.upper()-dist.lower()+1);
}

template <typename InputType, typename ValueType, typename Policy>
inline InputType quantile(const
discrete_uniform_distribution<InputType, ValueType, Policy>& dist,
const ValueType& p)
{
  return p*(dist.upper()-dist.lower()+1)+dist.lower()-1;
}

// Continuous Uniform Distribution

template <typename InputType, typename ValueType, typename Policy>
inline ValueType pdf(const continuous_uniform_distribution<InputType,
ValueType, Policy>& dist, const InputType& x)
{
  return ValueType(1.0)/(dist.upper()-dist.lower());
}

template <typename InputType, typename ValueType, typename Policy>
inline ValueType cdf(const continuous_uniform_distribution<InputType,
ValueType, Policy>& dist, const InputType& q)
{
  if (q <= dist.lower()) return 0;
  if (q >= dist.upper()) return 1;

  return (q-dist.lower())/ValueType(dist.upper()-dist.lower());
}

template <typename InputType, typename ValueType, typename Policy>
inline InputType quantile(const
continuous_uniform_distribution<InputType, ValueType, Policy>& dist,
const ValueType& p)
{
  return p*(dist.upper()-dist.lower())+dist.lower();
}

// and so on...
--- [/code_snip] ---

Cheers,

-- Marco