Summary Statistics Task Computation
Routines
Task computation routines calculate statistical
estimates on the data provided and parameters held in the task descriptor.
After you create the task and initialize its parameters, you can call the
computation routines as many times as necessary.
Table
"Summary Statistics Estimates Obtained with
lists the
vslSSCompute
Routine"respective
statistical estimates.
The Summary Statistics computation routines do not
signal floating-point errors, such as overflow or gradual underflow, or
operations with
NaNs
(except for the
missing values in the observations).
Estimate
| Support of Observations Available in Blocks
| Description
|
|---|---|---|
VSL_SS_MEAN | Yes
| Computes the array of means.
|
VSL_SS_SUM | Yes
| Computes the array of sums.
|
VSL_SS_2R_MOM | Yes
| Computes the array of the 2 nd order raw moments.
|
VSL_SS_2R_SUM | Yes
| Computes the array of raw sums of the 2 nd order.
|
VSL_SS_3R_MOM | Yes
| Computes the array of the 3 rd order raw moments.
|
VSL_SS_3R_SUM | Yes
| Computes the array of raw sums of the 3 rd order.
|
VSL_SS_4R_MOM | Yes
| Computes the array of the 4 th order raw moments.
|
VSL_SS_4R_SUM | Yes
| Computes the array of raw sums of the 4 th order.
|
VSL_SS_2C_MOM | Yes
| Computes the array of the 2 nd order central moments.
|
VSL_SS_2C_SUM | Yes
| Computes the array of central sums of the
2 nd order.
|
VSL_SS_3C_MOM | Yes
| Computes the array of the 3 rd order central moments.
|
VSL_SS_3C_SUM | Yes
| Computes the array of central sums of the
3 rd order.
|
VSL_SS_4C_MOM | Yes
| Computes the array of the 4 th order central moments.
|
VSL_SS_4C_SUM | Yes
| Computes the array of central sums of the
4 th order.
|
VSL_SS_KURTOSIS | Yes
| Computes the array of kurtosis values.
|
VSL_SS_SKEWNESS | Yes
| Computes the array of skewness values.
|
VSL_SS_MIN | Yes
| Computes the array of minimum values.
|
VSL_SS_MAX | Yes
| Computes the array of maximum values.
|
VSL_SS_VARIATION | Yes
| Computes the array of variation coefficients.
|
VSL_SS_COV | Yes
| Computes a covariance matrix.
|
VSL_SS_COR | Yes
| Computes a correlation matrix. The main
diagonal of the correlation matrix holds variances of the random vector
components.
|
VSL_SS_CP | Yes
| Computes a cross-product matrix.
|
VSL_SS_POOLED_COV | No
| Computes a pooled covariance matrix.
|
VSL_SS_POOLED_MEAN | No
| Computes an array of pooled means.
|
VSL_SS_GROUP_COV | No
| Computes group covariance matrices.
|
VSL_SS_GROUP_MEAN | No
| Computes group means.
|
VSL_SS_QUANTS | No
| Computes quantiles.
|
VSL_SS_ORDER_STATS | No
| Computes order statistics.
|
VSL_SS_ROBUST_COV | No
| Computes a robust covariance matrix.
|
VSL_SS_OUTLIERS | No
| Detects outliers in the dataset.
|
VSL_SS_PARTIAL_COV | No
| Computes a partial covariance matrix.
|
VSL_SS_PARTIAL_COR | No
| Computes a partial correlation matrix.
|
VSL_SS_MISSING_VALS | No
| Supports missing values in datasets.
|
VSL_SS_PARAMTR_COR | No
| Computes a parameterized correlation matrix.
|
VSL_SS_STREAM_QUANTS | Yes
| Computes quantiles for streaming data.
|
VSL_SS_MDAD | No
| Computes median absolute deviation.
|
VSL_SS_MNAD | No
| Computes mean absolute deviation.
|
VSL_SS_SORTED_OBSERV | No
| Sorts the dataset by the components of the random vector
ξ .
|
Table
. See the Summary Statistics Application Notes document [SS
Notes] for a detailed description of the methods.
"Summary Statistics Computation
Method"
lists estimate calculation methods supported by Intel® oneAPI Math Kernel Library
Intel® oneAPI Math Kernel Library
Method
| Description
|
|---|---|
VSL_SS_METHOD_FAST | Fast method for calculation of the estimates:
|
VSL_SS_METHOD_FAST_USER_MEAN | Fast method for calculation of the estimates
given user-defined mean:
|
VSL_SS_METHOD_1PASS | One-pass method for calculation of estimates:
|
VSL_SS_METHOD_TBS | TBS method for robust estimation of covariance
and mean
|
VSL_SS_METHOD_BACON | BACON method for detection of multivariate
outliers
|
VSL_SS_METHOD_MI | Multiple imputation method for support of
missing values
|
VSL_SS_METHOD_SD | Spectral decomposition method for
parameterization of a correlation matrix
|
VSL_SS_METHOD_SQUANTS_ZW | Zhang-Wang (ZW) method for quantile estimation
for streaming data
|
VSL_SS_METHOD_SQUANTS_ZW_FAST | Fast ZW method for quantile estimation for
streaming data
|
VSL_SS_METHOD_RADIX | Radix method for dataset sorting
|
You can calculate all requested estimates in one call
of the routine. For example, to compute a kurtosis and covariance matrix using
a fast method, pass a combination of the pre-defined parameters into the
Compute
routine as
shown in the example below:
... method = VSL_SS_METHOD_FAST; task_params = VSL_SS_KURTOSIS|VSL_SS_COV; … status = vsldSSCompute( task, task_params, method );
To compute statistical estimates for the next block of
observations, you can do one of the following:
Summary Statistics estimators.
- copy the observations to memory, starting with the address available to the task
- use one of the appropriate Editors to modify the pointer to the new dataset in the task.
"Summary Statistics Estimates Obtained with
for information on such observations supported by the vslSSCompute
Routine"Intel® oneAPI Math Kernel Library
To modify parameters of the task using the Task
Editors, set the address of the targeted matrix of the observations or change
the respective vector component indices. After you complete editing the task
parameters, you can compute statistical estimates in the modified environment.
If the task completes successfully, the computation
routine returns the zero status code. If an error is detected, the computation
routine returns an error code. In particular, an error status code is returned
in the following cases:
- the task pointer isNULL
- memory allocation has failed
- the calculation has failed for some other reason
You can use the
NULL
task pointer in calls to
editor routines. In this case, the routine is terminated and no system crash
occurs.