g01atc calculates the mean, standard deviation, coefficients of skewness and kurtosis, and the maximum and minimum values for a set of (optionally weighted) data. The input data can be split into arbitrary sized blocks, allowing large datasets to be summarised.
On entry: the number of valid observations processed so far, that is the number of observations with
, for . On the first call to g01atc, or when starting to summarise a new dataset, pn must be set to .
If , it must be the same value as returned by the last call to g01atc.
On exit: the updated number of valid observations processed, that is the number of observations with
, for .
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
On entry, .
Constraint: if then
, for .
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
On entry, .
On exit from previous call, .
Constraint: if , pn must be unchanged since previous call.
On exit we were unable to calculate xskew or xkurt. A value of has been returned.
8Parallelism and Performance
Background information to multithreading can be found in the Multithreading documentation.
g01atc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.
Both g01atc and g01auc consolidate results from multiple summaries. Whereas the former can only be used to combine summaries calculated sequentially, the latter combines summaries calculated in an arbitrary order allowing, for example, summaries calculated on different processing units to be combined.
This example summarises some simulated data. The data is supplied in three blocks, the first consisting of observations, the second observations and the last observations.