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Provides functions for fast matrix inversion, creation of empirical CDF from sample data including handling of asymmetric errors, and fitting to a funtion using chi-squared. The fitting procedure return the full covariance matrix describing the fitted parameters.
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lib/distributions/uniform.ex
defmodule Distribution.Uniform do
# Copyright 2019 Pieter Rijken
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
@moduledoc """
Provides the Uniform distribution.
"""
defstruct [:pars]
@type t() :: %__MODULE__{
pars: [number()] | {number,number}
}
end
defimpl Distribution, for: Distribution.Uniform do
import Distribution.Uniform
alias Distribution.Uniform
@spec uniform(Keyword.t) :: ((...) -> number)
defp uniform([]), do: uniform(0, 2.0)
defp uniform([avg: average]), do: uniform(0,2*average)
defp uniform(list) when is_list(list), do: fn () -> Enum.random(list) end
defp uniform(range = %Range{}), do: fn () -> Enum.random(range) end
@spec uniform(min::integer(),max::integer()) :: ((...) -> number)
defp uniform(min,max) when max>=min, do: fn () -> random(min,max) end
@spec random(min::number(),max::number()) :: number()
defp random(min,max) when max >= min do
min + (max-min)*:rand.uniform()
end
def skewness(%Uniform{}), do: raise Distribution.FunctionNotSupportedError, message: "skewness is not supported for the Uniform distribution"
def kurtosis(%Uniform{}), do: raise Distribution.FunctionNotSupportedError, message: "kurtosis is not supported for the Uniform distribution"
def size(%Uniform{}), do: 1
def cdf(%Uniform{}), do: raise Distribution.FunctionNotSupportedError, message: "cdf is not supported for the Uniform distribution"
def pdf(%Uniform{}), do: raise Distribution.FunctionNotSupportedError, message: "pdf is not supported for the Uniform distribution"
@doc """
## Examples:
iex> :rand.seed :exsplus, {101, 102, 103}
iex> random %Distribution.Uniform{pars: {0,20}}
14.897380811651171
iex> random %Distribution.Uniform{pars: 0..20}
11
iex> random %Distribution.Uniform{pars: [1,2,3,4,5]}
1
"""
def random(%Uniform{pars: {min,max}}), do: uniform(min,max).()
def random(%Uniform{pars: r=%Range{}}), do: uniform(r).()
def random(%Uniform{pars: list}), do: uniform(list).()
def random(%Uniform{}), do: uniform([]).()
end