| Name : R-gSEM
| |
| Version : 0.4.3.4
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.14.5
| Date : 2024-06-14 12:08:48
|
| Group : Development/Libraries/Other
| Source RPM : R-gSEM-0.4.3.4-lp153.14.5.src.rpm
|
| Size : 0.11 MB
| |
| Packager : (none)
| |
| Summary : Semi-Supervised Generalized Structural Equation Modeling
|
Description :
Conducts a semi-gSEM statistical analysis (semi-supervised generalized
structural equation modeling) on a data frame of coincident
observations of multiple predictive or intermediate variables and a
final continuous, outcome variable, via two functions sgSEMp1() and
sgSEMp2(), representing fittings based on two statistical principles.
Principle 1 determines all sensible univariate relationships in the
spirit of the Markovian process. The relationship between each pair of
variables, including predictors and the final outcome variable, is
determined with the Markovian property that the value of the current
predictor is sufficient in relating to the next level variable, i.e.,
the relationship is independent of the specific value of the
preceding-level variables to the current predictor, given the current
value. Principle 2 resembles the multiple regression principle in the
way multiple predictors are considered simultaneously. Specifically,
the relationship of the first-level predictors (such as Time and
irradiance etc) to the outcome variable (such as, module degradation or
yellowing) is fit by a supervised additive model. Then each significant
intermediate variable is taken as the new outcome variable and the
other variables (except the final outcome variable) as the predictors
in investigating the next-level multivariate relationship by a
supervised additive model. This fitting process is continued until all
sensible models are investigated.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
