Univariate statistics

Functions
template<std::floating_point T, stats Stats = stats::variance, std::random_access_iterator I, typename F = std::identity> requires concepts::arithmetic_projection<F, std::iter_value_t<I>>
auto	accumulate (I first, I last, F &&f=F {}) noexcept -> univariate_statistics
template<std::floating_point T, stats Stats = stats::variance, std::random_access_iterator I, std::random_access_iterator J, typename F = std::identity> requires concepts::arithmetic_projection<F, std::iter_value_t<I>>
and std::is_arithmetic_v< std::iter_value_t< J > > auto	accumulate (I first1, I last1, J first2, F &&f=F {}) noexcept -> univariate_statistics
template<std::floating_point T, stats Stats = stats::variance, nan_policy Policy = nan_policy::propagate, std::random_access_iterator I, std::random_access_iterator J, typename BinaryOp , typename F1 = std::identity, typename F2 = std::identity> requires std::is_invocable_v<F1, std::iter_value_t<I>>
and std::is_invocable_v< F2, std::iter_value_t< J > > and std::is_invocable_v< BinaryOp, std::invoke_result_t< F1, std::iter_value_t< I > >, std::invoke_result_t< F2, std::iter_value_t< J > > > and concepts::arithmetic_projection< BinaryOp, std::invoke_result_t< F1, std::iter_value_t< I > >, std::invoke_result_t< F2, std::iter_value_t< J > > > auto	accumulate (I first1, I last1, J first2, BinaryOp &&op=BinaryOp {}, F1 &&f1=F1 {}, F2 &&f2=F2 {}) noexcept -> std::conditional_t< Policy==nan_policy::omit, std::pair< univariate_statistics, std::size_t >, univariate_statistics >
template<std::floating_point T, stats Stats = stats::variance, nan_policy Policy = nan_policy::propagate, std::random_access_iterator I, std::random_access_iterator J, std::random_access_iterator K, typename BinaryOp , typename F1 = std::identity, typename F2 = std::identity> requires std::is_arithmetic_v<std::iter_value_t<K>> && std::is_invocable_v<F1, std::iter_value_t<I>> && std::is_invocable_v<F2, std::iter_value_t<J>> && std::is_invocable_v<BinaryOp, std::invoke_result_t<F1, std::iter_value_t<I>>, std::invoke_result_t<F2, std::iter_value_t<J>>> && concepts::arithmetic_projection<BinaryOp, std::invoke_result_t<F1, std::iter_value_t<I>>, std::invoke_result_t<F2, std::iter_value_t<J>>>
auto	accumulate (I first1, I last1, J first2, K first3, BinaryOp &&op=BinaryOp {}, F1 &&f1=F1 {}, F2 &&f2=F2 {}) noexcept -> std::conditional_t< Policy==nan_policy::omit, std::pair< univariate_statistics, std::size_t >, univariate_statistics >

Detailed Description

Methods for univariate statistics.

Function Documentation

accumulate() [1/4]

template<std::floating_point T, stats Stats = stats::variance, std::random_access_iterator I, typename F = std::identity>
requires concepts::arithmetic_projection<F, std::iter_value_t<I>>

auto accumulate ( I  first, I  last, F &&  f = F {}  ) -> univariate_statistics

inlinenoexcept

Accumulates a sequence of (projected) values.

Template Parameters

T	The scalar value type underlying the eve::wide<T> SIMD type used to compute the stats.

Parameters

first	The begin iterator for the first sequence
last	The end iterator for the first sequence
f	A projection mapping std::iter_value_t<I> to a scalar value

accumulate() [2/4]

template<std::floating_point T, stats Stats = stats::variance, nan_policy Policy = nan_policy::propagate, std::random_access_iterator I, std::random_access_iterator J, typename BinaryOp , typename F1 = std::identity, typename F2 = std::identity>
requires std::is_invocable_v<F1, std::iter_value_t<I>>

and std::is_invocable_v< F2, std::iter_value_t< J > > and std::is_invocable_v< BinaryOp, std::invoke_result_t< F1, std::iter_value_t< I > >, std::invoke_result_t< F2, std::iter_value_t< J > > > and concepts::arithmetic_projection< BinaryOp, std::invoke_result_t< F1, std::iter_value_t< I > >, std::invoke_result_t< F2, std::iter_value_t< J > > > auto accumulate ( I  first1, I  last1, J  first2, BinaryOp &&  op = BinaryOp {}, F1 &&  f1 = F1 {}, F2 &&  f2 = F2 {}  ) -> std::conditional_t<Policy == nan_policy::omit, std::pair<univariate_statistics, std::size_t>, univariate_statistics>

inlinenoexcept

Accumulates over the projected values from applying BinaryOp on the input sequences.

Template Parameters

T	The scalar value type underlying the eve::wide<T> SIMD type used to compute the stats
Stats	Which stats to compute
Policy	nan_policy::propagate (default): a non-finite projected value poisons the whole result, like the rest of this library. nan_policy::omit: positions where either raw input is non-finite are skipped (zero-weighted) instead, and the count of skipped pairs is additionally returned.
BinaryOp	Binary projection \(op(a,b) \to c\)
F1	Unary projection \(f(x_1) \to a\)
F2	Unary projection \(f(x_2) \to b\)

Parameters

first1	The begin iterator for the first sequence
last1	The end iterator for the first sequence
first2	The begin iterator for the second sequence
op	A binary projection mapping a tuple \((f_1(\cdot), f_2(\cdot))\) to a scalar value
f1	A projection mapping std::iter_value_t<I> to a scalar value
f2	A projection mapping std::iter_value_t<J> to a scalar value

Returns

nan_policy::propagate: the accumulated statistics. nan_policy::omit: the accumulated statistics over finite pairs, and the count of skipped (non-finite) pairs.

accumulate() [3/4]

template<std::floating_point T, stats Stats = stats::variance, std::random_access_iterator I, std::random_access_iterator J, typename F = std::identity>
requires concepts::arithmetic_projection<F, std::iter_value_t<I>>

and std::is_arithmetic_v< std::iter_value_t< J > > auto accumulate ( I  first1, I  last1, J  first2, F &&  f = F {}  ) -> univariate_statistics

inlinenoexcept

Accumulates a sequence of (projected) values.

Template Parameters

T	The scalar value type underlying the eve::wide<T> SIMD type used to compute the stats.

Parameters

first1	The begin iterator for the first sequence
last1	The end iterator for the first sequence
first2	The begin iterator for the second (weights) sequence
f	A projection mapping std::iter_value_t<I> to a scalar value

accumulate() [4/4]

template<std::floating_point T, stats Stats = stats::variance, nan_policy Policy = nan_policy::propagate, std::random_access_iterator I, std::random_access_iterator J, std::random_access_iterator K, typename BinaryOp , typename F1 = std::identity, typename F2 = std::identity>
requires std::is_arithmetic_v<std::iter_value_t<K>> && std::is_invocable_v<F1, std::iter_value_t<I>> && std::is_invocable_v<F2, std::iter_value_t<J>> && std::is_invocable_v<BinaryOp, std::invoke_result_t<F1, std::iter_value_t<I>>, std::invoke_result_t<F2, std::iter_value_t<J>>> && concepts::arithmetic_projection<BinaryOp, std::invoke_result_t<F1, std::iter_value_t<I>>, std::invoke_result_t<F2, std::iter_value_t<J>>>

auto accumulate ( I  first1, I  last1, J  first2, K  first3, BinaryOp &&  op = BinaryOp {}, F1 &&  f1 = F1 {}, F2 &&  f2 = F2 {}  ) -> std::conditional_t<Policy == nan_policy::omit, std::pair<univariate_statistics, std::size_t>, univariate_statistics>

inlinenoexcept

Weighted variant of accumulate (BinaryOp overload): folds a caller-supplied weight in, and (under nan_policy::omit) into the finite mask (‘w’ = finite ? w : 0`) instead of a flat 0/1 weight.

Parameters

first3

The begin iterator for the caller-supplied weights