53 lines
1.2 KiB
R
53 lines
1.2 KiB
R
# %%
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library(profoc)
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library(ggplot2)
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library(tidyr)
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library(dplyr)
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library(readr)
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# Creating faceted plots for different knot values and mu values
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# Create a function to generate the data for a given number of knots and mu value
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generate_basis_data <- function(num_knots, mu_value) {
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B <- profoc:::make_basis_matrix(1:99 / 100,
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profoc::make_knots(
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n = num_knots,
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mu = mu_value,
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sig = 1,
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nonc = 0,
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deg = 1
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),
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deg = 3
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)
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df <- as.data.frame(as.matrix(B))
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df$x <- 1:99 / 100
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df_long <- pivot_longer(df,
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cols = -x,
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names_to = "b",
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values_to = "y"
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)
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df_long$knots <- num_knots # Store knot count as numeric
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df_long$mu <- mu_value # Add mu parameter information
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return(df_long)
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}
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# Generate data for each combination of knot value and mu value
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knot_values <- 5:10
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mu_values <- seq(0.1, 0.9, by = 0.1)
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# Create an empty list to store all combinations
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all_data <- list()
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counter <- 1
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# Generate data for all combinations
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for (k in knot_values) {
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for (m in mu_values) {
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all_data[[counter]] <- generate_basis_data(k, m)
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counter <- counter + 1
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}
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}
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# Combine all data frames
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all_data <- bind_rows(all_data)
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write_csv(all_data, "basis_functions.csv")
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