
Plot method for model.predict functions
# S3 method for model.predict
plot(x, xvar = "", facet_row = ".",
facet_col = ".", color = "none", conf_lev = 0.95, ...)
Return value from predict functions (e.g., predict.regress)
Variable to display along the X-axis of the plot
Create vertically arranged subplots for each level of the selected factor variable
Create horizontally arranged subplots for each level of the selected factor variable
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
Confidence level to use for prediction intervals (.95 is the default)
further arguments passed to or from other methods
predict.regress
to generate predictions
predict.logistic
to generate predictions
# NOT RUN {
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")
# }
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