skewness¶
Entry point to compute skewness.
Description and Assumptions
The oneapi::mkl::stats::skewness function is used to compute a skewness array (skewness for each dataset’s dimension).
skewness supports the following precisions for data:
T
float
double
skewness (buffer version)¶
Syntax
namespace oneapi::mkl::stats {
template<method Method = method::fast, typename Type, layout ObservationsLayout>
void skewness(sycl::queue& queue,
const dataset<ObservationsLayout, sycl::buffer<Type, 1>>& data,
sycl::buffer<Type, 1> skewness);
}
Template Parameters
- Method
Method which is used for estimate computation. The specific values are as follows:
oneapi::mkl::stats::method::fastoneapi::mkl::stats::method::one_pass
- Type
Data precision.
- ObservationsLayout
Data layout. The specific values are described in dataset.
Input Parameters
- queue
The queue where the routine should be executed.
- data
Dataset which is used for computation.
Output Parameters
- skewness
sycl::buffer array of skewness values.
Throws
- oneapi::mkl::invalid_argument
Exception is thrown when skewness.get_count() == 0, or dataset object is invalid
skewness (USM version)¶
Syntax
namespace oneapi::mkl::stats {
template<method Method = method::fast, typename Type, layout ObservationsLayout>
sycl::event skewness(sycl::queue& queue,
const dataset<ObservationsLayout, Type*>& data,
Type* skewness,
const std::vector<sycl::event> &dependencies = {});
}
Template Parameters
- Method
Method which is used for estimate computation. The specific values are as follows:
oneapi::mkl::stats::method::fastoneapi::mkl::stats::method::one_pass
- Type
Data precision.
- ObservationsLayout
Data layout. The specific values are described in dataset.
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.
Output Parameters
- skewness
Pointer to the array of skewness values.
Throws
- oneapi::mkl::invalid_argument
Exception is thrown when skewness == nullptr, or dataset object is invalid
Return Value
Output event to wait on to ensure computation is complete.
Parent topic: Summary Statistics Routines