Plot method for model.predict functions
# S3 method for model.predict plot( x, xvar = "", facet_row = ".", facet_col = ".", color = "none", conf_lev = 0.95, ... )
Arguments
| x | Return value from predict functions (e.g., predict.regress) |
|---|---|
| xvar | Variable to display along the X-axis of the plot |
| facet_row | Create vertically arranged subplots for each level of the selected factor variable |
| facet_col | Create horizontally arranged subplots for each level of the selected factor variable |
| color | Adds color to a scatter plot to generate a heat map. For a line plot one line is created for each group and each is assigned a different color |
| conf_lev | Confidence level to use for prediction intervals (.95 is the default) |
| ... | further arguments passed to or from other methods |
See also
predict.regress to generate predictions
predict.logistic to generate predictions
Examples
regress(diamonds, "price", c("carat", "clarity")) %>% predict(pred_cmd = "carat = 1:10") %>% plot(xvar = "carat")logistic(titanic, "survived", c("pclass", "sex", "age"), lev = "Yes") %>% predict(pred_cmd = c("pclass = levels(pclass)", "sex = levels(sex)", "age = 0:100")) %>% plot(xvar = "age", color = "sex", facet_col = "pclass")
