| Name : R-NonParRolCor
| |
| Version : 0.8.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.3.4
| Date : 2024-06-14 11:34:01
|
| Group : Development/Libraries/Other
| Source RPM : R-NonParRolCor-0.8.0-lp153.3.4.src.rpm
|
| Size : 0.09 MB
| |
| Packager : (none)
| |
| Summary : a Non-Parametric Statistical Significance Test for Rolling Window Correlation
|
Description :
Estimates and plots (as a single plot and as a heat map) the rolling
window correlation coefficients between two time series and computes
their statistical significance, which is carried out through a
non-parametric computing-intensive method. This method addresses the
effects due to the multiple testing (inflation of the Type I error)
when the statistical significance is estimated for the rolling window
correlation coefficients. The method is based on Monte Carlo
simulations by permuting one of the variables (e.g., the dependent)
under analysis and keeping fixed the other variable (e.g., the
independent). We improve the computational efficiency of this method to
reduce the computation time through parallel computing. The
\'NonParRolCor\' package also provides examples with synthetic and
real-life environmental time series to exemplify its use. Methods
derived from R. Telford (2013)
< https://quantpalaeo.wordpress.com/2013/01/04/> and J.M.
Polanco-Martinez and J.L. Lopez-Martinez (2021)
< doi:10.1016/j.ecoinf.2021.101379>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
