nauf-package | Regression with NA values in unordered factors. |
anova.nauf.glmerMod | Type III anovas for mixed effects 'nauf' models. |
anova.nauf.lmerMod | Type III anovas for mixed effects 'nauf' models. |
anova.nauf.merMod | Type III anovas for mixed effects 'nauf' models. |
as.array.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
as.data.frame.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
as.data.frame.summ.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
as.matrix.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
as.shinystan-method | Create a shinystan object for posterior marginal means from nauf models. |
as.shinystan-method | Create a shinystan object from a nauf.stanreg model. |
fricatives | Catalan and Spanish intervocalic alveolar fricatives. |
nauf | Regression with NA values in unordered factors. |
nauf-pmmeans | Predicted marginal means for 'nauf' models. |
nauf.glmerMod | Class for fitted mixed effects models with 'nauf' contrasts. |
nauf.glmerMod-class | Class for fitted mixed effects models with 'nauf' contrasts. |
nauf.lmerMod | Class for fitted mixed effects models with 'nauf' contrasts. |
nauf.lmerMod-class | Class for fitted mixed effects models with 'nauf' contrasts. |
nauf.merMod | Class for fitted mixed effects models with 'nauf' contrasts. |
nauf.pmm.list | List of predicted marginal means objects for 'nauf' models. |
nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
nauf.stanreg | Class for fitted Bayesian models with 'nauf' contrasts. |
nauf.terms | Class for 'terms' objects which contain information about 'nauf' contrasts. |
nauf_contrasts | Not applicable unordered factor contrasts. |
nauf_glFormula | Create a model frame and fixed and random effects model matrices using 'nauf' contrasts. |
nauf_glm | Fit a fixed effects regression using 'nauf' contrasts. |
nauf_glm.nb | Fit a fixed effects regression using 'nauf' contrasts. |
nauf_glmer | Fit a mixed effects regression using 'nauf' contrasts. |
nauf_glmer.nb | Fit a mixed effects regression using 'nauf' contrasts. |
nauf_kfold | Cross-validation for 'nauf.stanreg' models. |
nauf_lFormula | Create a model frame and fixed and random effects model matrices using 'nauf' contrasts. |
nauf_lm | Fit a fixed effects regression using 'nauf' contrasts. |
nauf_lmer | Fit a mixed effects regression using 'nauf' contrasts. |
nauf_model.frame | Create a model frame using 'nauf' contrasts. |
nauf_model.matrix | Create a fixed effects model matrix using 'nauf' contrasts. |
nauf_pmmeans | Predicted marginal means for 'nauf' models. |
nauf_ref.grid | Predicted marginal means for 'nauf' models. |
nauf_stan_glm | Fit a Bayesian fixed effects regression with 'nauf' contrasts. |
nauf_stan_glm.nb | Fit a Bayesian fixed effects regression with 'nauf' contrasts. |
nauf_stan_glmer | Fit a Bayesian mixed effects regression with 'nauf' contrasts. |
nauf_stan_glmer.nb | Fit a Bayesian mixed effects regression with 'nauf' contrasts. |
nauf_stan_lm | Fit a Bayesian fixed effects regression with 'nauf' contrasts. |
nauf_stan_lmer | Fit a Bayesian mixed effects regression with 'nauf' contrasts. |
plosives | Spanish intervocalic plosives. |
predict.nauf.glmerMod | Predictions from a mixed effects 'nauf' model at new data values. |
predict.nauf.lmerMod | Predictions from a mixed effects 'nauf' model at new data values. |
predict.nauf.merMod | Predictions from a mixed effects 'nauf' model at new data values. |
print.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
print.summ.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |
summary.nauf.pmm.stan | Posterior samples of marginal means from Bayesian 'nauf' models. |