I can provide a general outline of how to solve this problem.

Step 1: Preprocessing

• The data seems to be in a tabular format, with each row representing a single observation.
• The ..eq.label.. column likely contains the equation labels for the model.
• We need to preprocess the data by converting the equation labels into a standard format that can be used for analysis.

Step 2: Data Cleaning

• Check for missing or invalid values in the data and clean them accordingly.
• Ensure that all columns are of suitable data types (e.g., numeric, categorical).

Step 3: Model Specification

• Use the ggplot2 package to create a model specification.
• The geom_smooth() function can be used to specify the type of smoothing model to use (e.g., linear regression).
• We need to define the formula for the model using the ..eq.label.. column.

Step 4: Model Building

• Use the ggplot_build() function to build a data frame that contains all the necessary information for the plot.
• Define a custom function process_label() to process the equation labels and convert them into a standard format.

Step 5: Plotting

• Use the cowplot package to create a grid of plots.
• Define a new column in the data frame to hold the processed equation labels.
• Use the ggplot_gtable() function to create a grid table from the model specification.

Here’s some sample R code to get you started:

# Load necessary libraries
library(ggplot2)
library(cowplot)

# Load and preprocess data
data <- read.table("your_data.csv")

# Define custom function to process equation labels
process_label <- function(x) {
  gsub("~~~",")~~~",gsub(")~`=`~",")~`=`~exp(",x))
}

# Process equation labels
data$label <- lapply(data$..eq.label.., process_label)

# Create model specification
formula <- y ~ poly(x, 3, raw = TRUE)

# Build data frame for plot
gg_raw <- ggplot_build(ggplot(data, aes(x, y)) + 
                      geom_point() +
                      geom_smooth(method = "lm", formula = formula) +
                      stat_poly_eq(formula = y ~ x,
                                    aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~")),
                                    parse = TRUE, color = "black"))

# Create grid table
gtable <- ggplot_gtable(gg_raw)
cowplot::plot_grid(gtable)

Note that this is just a starting point, and you may need to modify the code to suit your specific needs.

Last modified on 2024-05-20