| averageR2w | For use in boottestgscm. |
| boottestgscm | Testing two segmentations of a GSC model |
| checkw | Checking composite based SE models if there are weights in accordance with the loadings and the covariance matrix of the composites |
| clustergscairls | Clustering gsc-models |
| FlDeriv | 'FlDeriv'compute the Jacobian of the Fleishman transform for a given set of coefficients b,c,d |
| Fleishman | 'Fleishman' computes the variance, skewness and kurtosis for a given set of of coefficients b,c,d for the Fleishman transform |
| FleishmanIC | Functions to generate nonnormal distributed multivariate random vectors with mean=0, var=1 and given correlations and coefficients of skewness and excess kurtosis. This is done with the method of Vale & Morelli: The coefficients of the Fleishman transform Y = -c + bX +cX^2 + dX^3 are computed. from given skewness gamma[1] = E(Y^3) and kurtosis gamma[2] = E(Y^4) - 3. A indermediate correlation matrix is computed from the desired correlation matrix and the Fleishman coefficients. A singular value decomposition of the indermediate correlation matrix is performed and a matrix of independend normal random numbers is generated and transformed into correlated ones. Finally the Fleishman transform is applied to the columns of this data matrix. |
| gscals | Estimating GSC models belonging to scenarios reflective-reflective, formative-reflective and formative-formative |
| gscalsout | Output of gscals for the simplemodel data. |
| gscalsresid | For use in clustergscairls, residuals of a gsc-model |
| gscmcov | Determination of the covariance matrix of a GSC model belonging to scenario 1, scenario 2, scenario 3 |
| gscmcovff | 'gscmcovff' determines the covariance matrix of a GSC model belonging to scenario ff. |
| gscmcovfr | 'gscmcovfr' determines the covariance matrix of a GSC model belonging to scenario fr. The covariance matrices of the errors are supposed to be diagonal. |
| gscmcovout | Output of covgscmodel for the simplemodel data. |
| gscmcovrr | 'gscmcovrr' determines the covariance matrix of a GSC model belonging to scenario rr. |
| mobi250 | Mobile phone data for the ECSI model. |
| NewtonFl | 'NewtonFl' Newton's method to find roots of the function FlFunc. |
| plspath | Estimation of pls-path models |
| poloecfree | Political and economical freedom. |
| rValeMaurelli | 'rValeMaurelli' Simulate data from a multivariate nonnormal distribution such that 1) Each marginal distribution has a specified skewness and kurtosis 2) The marginal variables have the correlation matrix R |
| simplemodel | Simulated data. |
| SolveCorr | 'SolveCorr' Solve the Vale-Maurelli cubic equation to find the intermediate correlation between two normal variables that gives rise to a target correlation (rho) between the two transformed nonnormal variables. |
| subcheckw | Function for use in checkw |
| twoclm | Simulated data. |
| VMTargetCorr | 'VMTargetCorr' Given a target correlation matrix, R, and target values of skewness and kurtosis for each marginal distribution, find the "intermediate" correlation matrix, V |