| psychonetrics-package | Structural Equation Modeling and Confirmatory Network Analysis | 
| addfit | Model updating functions | 
| addMIs | Model updating functions | 
| addSEs | Model updating functions | 
| aggregate_bootstraps | Aggregate Bootstrapped Models | 
| bifactor | Bi-factor models | 
| bootstrap | Bootstrap a psychonetrics model | 
| changedata | Change the data of a psychonetrics object | 
| checkFisher | Diagnostic functions | 
| checkJacobian | Diagnostic functions | 
| 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 | 
| fixstart | Attempt to Fix Starting Values | 
| 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 | 
| logbook | Retrieve the psychonetrics logbook | 
| 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"' | 
| psychonetrics_bootstrap-class | Class '"psychonetrics_bootstrap"' | 
| psychonetrics_log-class | Class '"psychonetrics"' | 
| psychonetrics_samplestats-class | Class '"psychonetrics"' | 
| resid-method | Class '"psychonetrics"' | 
| residuals-method | Class '"psychonetrics"' | 
| ri_clpm | Random intercept cross-lagged panel models | 
| ri_clpm_stationary | Random intercept cross-lagged panel models | 
| rnm | Continuous latent variable family of psychonetrics models | 
| runmodel | Run a psychonetrics model | 
| sessionInfo-class | Class '"psychonetrics"' | 
| setestimator | Convenience functions | 
| setoptimizer | Convenience functions | 
| setverbose | Should messages of computation progress be printed? | 
| show-method | Class '"psychonetrics"' | 
| show-method | Class '"psychonetrics_bootstrap"' | 
| show-method | Class '"psychonetrics"' | 
| simplestructure | Generate factor loadings matrix with simple structure | 
| StarWars | Star Wars dataset | 
| stepup | Stepup model search along modification indices | 
| transmod | Transform between model types | 
| 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 |