STATISTICS
Function
Statistics contains procedures for calculating correlation functions from time series data. At present this is done
with a direct method similar to that described in the book by Allen and Tildesley.
Dependencies
Module | Variables |
DEFINITIONS | DP |
Public Variables
None.
Public Procedures
There are two public subroutines in this module.
Subroutine | Purpose |
STATISTICS_ACF_DIRECT | Calculate an autocorrelation function. |
STATISTICS_CCF_DIRECT | Calculate a cross correlation function. |
STATISTICS_ACF_DIRECT
Argument | Type | Intent | Optional | Purpose |
X | Real(:) | In | No | The time series data. |
ACF | Real(0:) | Out | No | The autocorrelation function. |
NORMALIZED | Logical | In | Yes | A normalization flag. |
- STATISTICS_ACF_DIRECT calculates the autocorrelation function of the time series data in the array X and returns it in
the array ACF.
- The number of points to calculate in the correlation function is determined by as the minimum of the sizes of the
arrays ACF and X. Normally ACF will have a much smaller size than X.
- If the argument NORMALIZATION is present with the value .TRUE., the correlation function is normalized. The default is
not to normalize.
STATISTICS_CCF_DIRECT
Argument | Type | Intent | Optional | Purpose |
X | Real(:) | In | No | The time series data for the first property. |
Y | Real(:) | In | No | The time series data for the second property. |
CCF | Real(0:) | Out | No | The cross correlation function. |
NORMALIZED | Logical | In | Yes | A normalization flag. |
- STATISTICS_CCF_DIRECT calculates the cross correlation function of the time series data in the arrays X and Y and
returns it in the array CCF.
- The number of points to calculate in the correlation function is determined by as the minimum of the sizes of the
arrays CCF, X and Y. Normally CCF will have a much smaller size than either X or Y.
- If the argument NORMALIZATION is present with the value .TRUE., the correlation function is normalized. The default is
not to normalize.
Stability
Stable.