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| 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 |