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 "VSL Summary Statistics Estimates Obtained with Compute Routine" lists the respective statistical estimates.

Note iconNote

The VSL 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).

VSL Summary Statistics Estimates Obtained with Compute Routine

Estimate

Support of Observations Available in Blocks

Description

VSL_SS_MEAN

Yes

Computes the array of means.

VSL_SS_2R_MOM

Yes

Computes the array of the 2nd order raw moments.

VSL_SS_3R_MOM

Yes

Computes the array of the 3rd order raw moments.

VSL_SS_4R_MOM

Yes

Computes the array of the 4th order raw moments.

VSL_SS_2C_MOM

Yes

Computes the array of the 2nd order central moments.

VSL_SS_3C_MOM

Yes

Computes the array of the 3rd order central moments.

VSL_SS_4C_MOM

Yes

Computes the array of the 4th order central moments.

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.

VSL_SS_POOLED_COV

No

Computes a pooled covariance matrix.

VSL_SS_GROUP_COV

No

Computes group covariance matrices.

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.

Table "VSL Summary Statistics Computation Methods" lists estimate calculation methods supported by Intel MKL. See the Intel(R) MKL Summary Statistics Library Application Notes document on the Intel® MKL web page for a detailed description of the methods.

VSL Summary Statistics Computation Method

Method

Description

VSL_SS_METHOD_FAST

Fast method for calculation of the estimates

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

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:

The library does not detect your changes of the dataset and computed statistical estimates. To obtain statistical estimates for a new matrix, change the observations and initialize relevant arrays. You can follow this procedure to compute statistical estimates for observations that come in portions. See Table "VSL Summary Statistics Estimates Obtained with Compute Routine" for information on such observations supported by the Intel MKL VSL Summary Statistics estimators.

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:

Note iconNote

You can use the NULL task pointer in calls to editor routines. In this case, the routine is terminated and no system crash occurs.


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