.. SPDX-FileCopyrightText: 2019-2020 Intel Corporation .. .. SPDX-License-Identifier: CC-BY-4.0 .. _onemkl_stats_skewness: skewness ======== Entry point to compute skewness. .. _onemkl_stats_skewness_description: .. rubric:: Description and Assumptions The oneapi::mkl::stats::skewness function is used to compute a skewness array (skewness for each dataset's dimension). :ref:`onemkl_stats_skewness` supports the following precisions for data: .. list-table:: :header-rows: 1 * - T * - ``float`` * - ``double`` .. _onemkl_stats_skewness_buffer: skewness (buffer version) ------------------------- .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::stats { template void skewness(sycl::queue& queue, const dataset>& data, sycl::buffer skewness); } .. container:: section .. rubric:: Template Parameters Method Method which is used for estimate computation. The specific values are as follows: * ``oneapi::mkl::stats::method::fast`` * ``oneapi::mkl::stats::method::one_pass`` Type Data precision. ObservationsLayout Data layout. The specific values are described in :ref:`onemkl_stats_dataset`. .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. data Dataset which is used for computation. .. container:: section .. rubric:: Output Parameters skewness sycl::buffer array of skewness values. .. container:: section .. rubric:: Throws oneapi::mkl::invalid_argument Exception is thrown when skewness.get_count() == 0, or dataset object is invalid .. _onemkl_stats_skewness_usm: skewness (USM version) ---------------------- .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::stats { template sycl::event skewness(sycl::queue& queue, const dataset& data, Type* skewness, const std::vector &dependencies = {}); } .. container:: section .. rubric:: Template Parameters Method Method which is used for estimate computation. The specific values are as follows: * ``oneapi::mkl::stats::method::fast`` * ``oneapi::mkl::stats::method::one_pass`` Type Data precision. ObservationsLayout Data layout. The specific values are described in :ref:`onemkl_stats_dataset`. .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. data Dataset which is used for computation. dependencies Optional parameter. List of events to wait for before starting computation, if any. .. container:: section .. rubric:: Output Parameters skewness Pointer to the array of skewness values. .. container:: section .. rubric:: Throws oneapi::mkl::invalid_argument Exception is thrown when skewness == nullptr, or dataset object is invalid .. container:: section .. rubric:: Return Value Output event to wait on to ensure computation is complete. **Parent topic:** :ref:`onemkl_stats_routines`