| psychonetrics-package | Structural Equation Modeling and Confirmatory Network Analysis |
| addfit | Model updating functions |
| addMIs | Model updating functions |
| addSEs | Model updating functions |
| bifactor | Bi-factor models |
| bootstrap | Bootstrap a psychonetrics model |
| changedata | Change the data of a psychonetrics object |
| cholesky | Variance-covariance family of psychonetrics models |
| CIplot | Plot Analytic Confidence Intervals |
| compare | Model comparison |
| corr | Variance-covariance family of psychonetrics models |
| covML | Maximum likelihood covariance estimate |
| covMLtoUB | Maximum likelihood covariance estimate |
| covUBtoML | Maximum likelihood covariance estimate |
| diagonalizationMatrix | Model matrices used in derivatives |
| dlvm1 | Lag-1 dynamic latent variable model family of psychonetrics models for panel data |
| duplicationMatrix | Model matrices used in derivatives |
| eliminationMatrix | Model matrices used in derivatives |
| emergencystart | Reset starting values to simple defaults |
| esa | Ergodic Subspace Analysis |
| esa_manual | Ergodic Subspace Analysis |
| factorscores | Compute factor scores |
| fit | Print fit indices |
| fixpar | Parameters modification |
| freepar | Parameters modification |
| generate | Generate data from a fitted psychonetrics object |
| getmatrix | Extract an estimated matrix |
| getVCOV | Obtain the asymptotic covariance matrix |
| ggm | Variance-covariance family of psychonetrics models |
| groupequal | Group equality constrains |
| groupfree | Group equality constrains |
| gvar | Lag-1 vector autoregression family of psychonetrics models |
| identify | Model updating functions |
| intersectionmodel | Unify models across groups |
| Ising | Ising model |
| Jonas | Jonas dataset |
| latentgrowth | Latnet growth curve model |
| lnm | Continuous latent variable family of psychonetrics models |
| lrnm | Continuous latent variable family of psychonetrics models |
| lvm | Continuous latent variable family of psychonetrics models |
| meta_ggm | Variance-covariance and GGM meta analysis |
| meta_varcov | Variance-covariance and GGM meta analysis |
| MIs | Print modification indices |
| ml_gvar | Multi-level Lag-1 dynamic latent variable model family of psychonetrics models for time-series data |
| ml_lnm | Multi-level latent variable model family |
| ml_lrnm | Multi-level latent variable model family |
| ml_lvm | Multi-level latent variable model family |
| ml_rnm | Multi-level latent variable model family |
| ml_tsdlvm1 | Multi-level Lag-1 dynamic latent variable model family of psychonetrics models for time-series data |
| ml_ts_lvgvar | Multi-level Lag-1 dynamic latent variable model family of psychonetrics models for time-series data |
| ml_var | Multi-level Lag-1 dynamic latent variable model family of psychonetrics models for time-series data |
| modelsearch | Stepwise model search |
| panelgvar | Lag-1 dynamic latent variable model family of psychonetrics models for panel data |
| panelvar | Lag-1 dynamic latent variable model family of psychonetrics models for panel data |
| panel_lvgvar | Lag-1 dynamic latent variable model family of psychonetrics models for panel data |
| parameters | Print parameter estimates |
| parequal | Set equality constrains across parameters |
| partialprune | Partial pruning of multi-group models |
| plot.esa | Ergodic Subspace Analysis |
| plot.esa_manual | Ergodic Subspace Analysis |
| prec | Variance-covariance family of psychonetrics models |
| precision | Variance-covariance family of psychonetrics models |
| print.esa | Ergodic Subspace Analysis |
| print.esa_manual | Ergodic Subspace Analysis |
| print.psychonetrics_compare | Model comparison |
| prune | Stepdown model search by pruning non-significant parameters. |
| psychonetrics | Structural Equation Modeling and Confirmatory Network Analysis |
| psychonetrics-class | Class '"psychonetrics"' |
| resid-method | Class '"psychonetrics"' |
| residuals-method | Class '"psychonetrics"' |
| rnm | Continuous latent variable family of psychonetrics models |
| runmodel | Run a psychonetrics model |
| setestimator | Convenience functions |
| setoptimizer | Convenience functions |
| setverbose | Should messages of computation progress be printed? |
| show-method | Class '"psychonetrics"' |
| simplestructure | Generate factor loadings matrix with simple structure |
| StarWars | Star Wars dataset |
| stepup | Stepup model search along modification indices |
| tsdlvm1 | Lag-1 dynamic latent variable model family of psychonetrics models for time-series data |
| ts_lvgvar | Lag-1 dynamic latent variable model family of psychonetrics models for time-series data |
| unionmodel | Unify models across groups |
| usecpp | Convenience functions |
| var1 | Lag-1 vector autoregression family of psychonetrics models |
| varcov | Variance-covariance family of psychonetrics models |