我想评估同一数据集上多个（主要是）线性回归模型的性能。我想也许使用tidymodels包和workflowsets::workflow_set()可能会起作用。我按照此处的示例进行操作，但我无法弄清楚如何从代码中实际获得拟合结果。
# Load packages
library("tidyverse")
library('workflowsets')
library("parsnip")
library("recipes")
# Data
dat <-
structure(list(q = c(66.65, 75.58, 83.06, 91.28, 119.26, 133.14,
146.32, 153.39, 168.57, 182.36, 210.09, 188.19, 213.42, 296.95,
326.33, 358.63, 475.99, 475.99, 683.44, 683.44, 838.49, 1282.1,
1648.97, 1572.97, 2055.14, 2521.39, 2685.11, 2859.46, 3242.87,
6899.19, 6377.42, 7581.96, 9599.32), c = c(317.06, 283.99, 279.56,
283.99, 227.84, 227.84, 262.5, 242.64, 270.9, 266.67, 210.6,
235.12, 235.12, 210.6, 207.31, 227.84, 220.78, 194.67, 177.13,
207.31, 179.94, 177.13, 182.79, 139.89, 148.98, …