| Name : R-ERP
| |
| Version : 2.2
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.3.9
| Date : 2024-06-14 11:33:22
|
| Group : Development/Libraries/Other
| Source RPM : R-ERP-2.2-lp153.3.9.src.rpm
|
| Size : 0.89 MB
| |
| Packager : (none)
| |
| Summary : Significance Analysis of Event-Related Potentials Data
|
Description :
Functions for signal detection and identification designed for
Event-Related Potentials (ERP) data in a linear model framework. The
functional F-test proposed in Causeur, Sheu, Perthame, Rufini (2018,
submitted) for analysis of variance issues in ERP designs is
implemented for signal detection (tests for mean difference among
groups of curves in One-way ANOVA designs for example). Once an
experimental effect is declared significant, identification of
significant intervals is achieved by the multiple testing procedures
reviewed and compared in Sheu, Perthame, Lee and Causeur (2016,
< DOI:10.1214/15-AOAS888>). Some of the methods gathered in the package
are the classical FDR- and FWER-controlling procedures, also available
using function p.adjust. The package also implements the
Guthrie-Buchwald procedure (Guthrie and Buchwald, 1991
< DOI:10.1111/j.1469-8986.1991.tb00417.x>), which accounts for the
auto-correlation among t-tests to control erroneous detection of short
intervals. The Adaptive Factor-Adjustment method is an extension of the
method described in Causeur, Chu, Hsieh and Sheu (2012,
< DOI:10.3758/s13428-012-0230-0>). It assumes a factor model for the
correlation among tests and combines adaptively the estimation of the
signal and the updating of the dependence modelling (see Sheu et al.,
2016, < DOI:10.1214/15-AOAS888> for further details).
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
