Function reference • modelbased

All functions
`as.numeric_ifnumeric()`	Convert to Numeric if Possible
`estimate_contrasts()`	Estimate contrasts between factor levels
`estimate_contrasts(<lm>)`	Estimate contrasts
`estimate_contrasts(<stanreg>)`	Estimate contrasts
`estimate_means()`	Estimate average value of response variable at each factor levels
`estimate_means(<lm>)`	Estimate marginal means
`estimate_means(<stanreg>)`	Estimate marginal means
`estimate_response()` `estimate_link()`	Generates predictions
`estimate_response(<glm>)` `estimate_link(<glm>)`	Generates predictions for Frequentist models
`estimate_response(<stanreg>)` `estimate_link(<stanreg>)` `estimate_response(<data.frame>)` `estimate_link(<data.frame>)`	Generates predictions for Bayesian models
`estimate_slopes()`	Estimate the slopes of a numeric predictor (over different factor levels)
`estimate_slopes(<lm>)`	Estimate the slopes of a numeric predictor (over different factor levels)
`estimate_slopes(<stanreg>)`	Estimate the slopes of a numeric predictor (over different factor levels)
`estimate_smooth()`	Describe the smooth term (for GAMs) or non-linear predictors
`estimate_smooth(<stanreg>)`	Describe the smooth term (for GAMs) or non-linear predictors
`find_inversions()`	Find points of inversion
`reshape_draws()`	Reshape estimations with Bayesian posterior draws to long format
`smoothing()`	Smoothing a vector or a time series
`visualisation_matrix()`	Create a reference grid
`zero_crossings()`	Find zero crossings of a vector

Reference