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_link | Generates predictions |
estimate_link.data.frame | Generates predictions for Bayesian models |
estimate_link.glm | Generates predictions for Frequentist models |
estimate_link.stanreg | Generates predictions for Bayesian models |
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 | Generates predictions |
estimate_response.data.frame | Generates predictions for Bayesian models |
estimate_response.glm | Generates predictions for Frequentist models |
estimate_response.stanreg | Generates predictions for Bayesian models |
estimate_slopes | Estimate the slopes of a numeric predictor (over different factor levels) |
estimate_slopes.glmmTMB | 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 |