Running variances from sparse data. More...

Public Member Functions
	RunningSparse (Index_ num, Output_ mean, Output_ variance, bool skip_nan, Index_ subtract=0)

void	add (const Value_ value, const Index_ index, Index_ number)

void	finish ()

Detailed Description

template<typename Output_, typename Value_, typename Index_>
class tatami_stats::variances::RunningSparse< Output_, Value_, Index_ >

Running variances from sparse data.

Compute running means and variances from sparse data using Welford's method. This does the same as RunningDense but for sparse observed vectors.

Template Parameters

Output_	Type of the output data.
Value_	Type of the input data.
Index_	Type of the row/column indices.

Constructor & Destructor Documentation

template<typename Output_ , typename Value_ , typename Index_ >

tatami_stats::variances::RunningSparse< Output_, Value_, Index_ >::RunningSparse	(	Index_	num,
		Output_ *	mean,
		Output_ *	variance,
		bool	skip_nan,
		Index_	subtract = `0`
	)

inline

Parameters

	num	Number of objective vectors.
[out]	mean	Pointer to an output array of length `num`, containing the means for each objective vector. This should be zeroed on input; after `finish()` is called, this will contain the mean for each objective vector.
[out]	variance	Pointer to an output array of length `num`, containing the variances for each objective vector. This should be zeroed on input; after `finish()` is called, this will contain the sample variance for each objective vector.
	skip_nan	See `Options::skip_nan` for details.
	subtract	Offset to subtract from each element of `index` before using it to index into `mean` and friends. Only relevant if `mean` and friends hold statistics for a contiguous subset of objective vectors, e.g., during task allocation for parallelization.

template<typename Output_ , typename Value_ , typename Index_ >

void tatami_stats::variances::RunningSparse< Output_, Value_, Index_ >::add	(	const Value_ *	value,
		const Index_ *	index,
		Index_	number
	)

inline

Add the next observed vector to the variance calculation.

Parameters

[in]	value	Value of structural non-zero elements.
[in]	index	Index of structural non-zero elements.
	number	Number of non-zero elements in `value` and `index`.

template<typename Output_ , typename Value_ , typename Index_ >

void tatami_stats::variances::RunningSparse< Output_, Value_, Index_ >::finish ( )

inline

Finish the variance calculation once all observed vectors have been passed to add().

The documentation for this class was generated from the following file: