Predict values based on a bestfit object.
# S3 method for bestfit predict( object, fit = 1, newdata = object$newdata, interval = c("none", "confidence", "prediction"), level = 0.8, ... )
| object | object of class |
|---|---|
| fit | The number of the chosen model from the combinations matrix (defaults for the best R2 model) |
| newdata | An optional data frame in which to look for variables with
which to predict. Defaults for the eventually existent "aval" data in data
frame used to build the |
| interval | Type of interval calculation. Can be abbreviated. Defaults to confidence interval |
| level | Tolerance/confidence level. Defaults for the standardized value in NBR-14.653-2 (80%) |
| ... | further arguments passed to predict.lm. |
dados <- st_drop_geometry(centro_2015) best_fit <- bestfit(valor ~ ., data = dados) p <- predict(best_fit, interval = "confidence")#> Error in is.data.frame(data): object 'dados' not foundp#> Error in eval(expr, envir, enclos): object 'p' not found