| Name : R-EMAR
| |
| Version : 1.0.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.4
| Date : 2024-06-14 11:00:04
|
| Group : Development/Libraries/Other
| Source RPM : R-EMAR-1.0.0-lp153.1.4.src.rpm
|
| Size : 0.02 MB
| |
| Packager : (none)
| |
| Summary : Empirical Model Assessment
|
Description :
A tool that allows users to generate various indices for evaluating
statistical models. The fitstat() function computes indices based on
the fitting data. The valstat() function computes indices based on the
validation data set. Both fitstat() and valstat() will return 16
indices SSR: residual sum of squares, TRE: total relative error, Bias:
mean bias, MRB: mean relative bias, MAB: mean absolute bias, MAPE: mean
absolute percentage error, MSE: mean squared error, RMSE: root mean
square error, Percent.RMSE: percentage root mean squared error, R2:
coefficient of determination, R2adj: adjusted coefficient of
determination, APC: Amemiya\'s prediction criterion, logL:
Log-likelihood, AIC: Akaike information criterion, AICc: corrected
Akaike information criterion, BIC: Bayesian information criterion, HQC:
Hannan-Quin information criterion. The lower the better for the SSR,
TRE, Bias, MRB, MAB, MAPE, MSE, RMSE, Percent.RMSE, APC, AIC, AICc, BIC
and HQC indices. The higher the better for R2 and R2adj indices. Petre
Stoica, P., Selén, Y. (2004) < doi:10.1109/MSP.2004.1311138>\
Zhou et
al. (2023) < doi:10.3389/fpls.2023.1186250>\
Ogana, F.N., Ercanli, I.
(2021) < doi:10.1007/s11676-021-01373-1>\
Musabbikhah et al. (2019)
< doi:10.1088/1742-6596/1175/1/012270>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
