gSEM: Semi-Supervised Generalized Structural Equation Modeling

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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.

Author
Junheng Ma <jxm216@case.edu>, Nicholas Wheeler <nrw16@case.edu>, Yifan Xu <ethan.yifanxu@case.edu>, Wenyu Du <wxd97@case.edu>, Abdulkerim Gok <axg515@case.edu>, Jiayang Sun <jiayang.sun@case.edu>
Date of publication
2016-01-11 21:18:40
Maintainer
Junheng Ma <jxm216@case.edu>
License
GPL (>= 2)
Version
0.4.3.4

View on CRAN

Man pages

acrylic
A data frame of an acrylic degradation experiment
genInit
Generate initial values for nls function
gSEM
Semi-supervised Generalized Structure Equation Modeling
path
Extract Path Coefficients
plot.sgSEMp1
Plotting of Principle 1 of Semi-gSEM
plot.sgSEMp2
Plotting of Principle 2 of Semi-gSEM
sgSEMp1
Semi-supervised Generalized Structural Equation Modelling...
sgSEMp2
Semi-supervised Generalized Structural Equation Modelling...
summary.sgSEMp1
Summary of Semi-gSEM
summary.sgSEMp2
Summary of Semi-gSEM

Files in this package

gSEM
gSEM/NAMESPACE
gSEM/data
gSEM/data/acrylic.RData
gSEM/R
gSEM/R/plot.sgSEMp2.R
gSEM/R/plot.sgSEMp1.R
gSEM/R/plotAll.R
gSEM/R/is.wholenumber.R
gSEM/R/path.R
gSEM/R/acrylic.R
gSEM/R/genInit.R
gSEM/R/summary.sgSEMp2.R
gSEM/R/summary.sgSEMp1.R
gSEM/R/cf.R
gSEM/R/gSEM.R
gSEM/R/sgSEMp2.R
gSEM/R/nlsR2.R
gSEM/R/print.sgSEMp1.R
gSEM/R/sgSEMp1.R
gSEM/MD5
gSEM/DESCRIPTION
gSEM/man
gSEM/man/acrylic.Rd
gSEM/man/summary.sgSEMp1.Rd
gSEM/man/plot.sgSEMp2.Rd
gSEM/man/path.Rd
gSEM/man/summary.sgSEMp2.Rd
gSEM/man/gSEM.Rd
gSEM/man/sgSEMp2.Rd
gSEM/man/sgSEMp1.Rd
gSEM/man/genInit.Rd
gSEM/man/plot.sgSEMp1.Rd