72 lines
1.8 KiB
R
72 lines
1.8 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, sig_value, nonc_value, tailw_value, deg_value) {
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grid <- seq(from = 0.01, to = 0.99, length.out = 50)
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# Use provided degree
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B <- profoc:::make_basis_matrix(grid,
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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 = sig_value,
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nonc = nonc_value,
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tailw = tailw_value,
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deg = deg_value
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),
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deg = deg_value
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)
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B_mat <- round(as.matrix(B),2)
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df <- as.data.frame(B_mat)
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df$x <- grid
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df_long <- pivot_longer(df,
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cols = -x,
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names_to = "b",
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values_to = "y"
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)
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df_long$knots <- num_knots
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df_long$mu <- mu_value
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df_long$sig <- sig_value
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df_long$nonc <- nonc_value
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df_long$tailw <- tailw_value
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df_long$deg <- deg_value
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return(df_long)
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}
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# Generate data for each combination of knot, mu, sig, nonc, tailw, and deg
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knot_values <- c(10)
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mu_values <- seq(0.1, 0.9, by = 0.2)
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sig_values <- 2^(-2:2)
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nonc_values <- c(-4,-2,0,2,4)
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tailw_values <- 2^(-2:2)
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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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# Nested loops to cover all parameter combinations
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for (k in knot_values) {
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print(paste("Processing knots:", k))
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for (m in mu_values) {
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print(paste("Processing mu:", m))
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for (s in sig_values) {
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for (nc in nonc_values) {
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for (tw in tailw_values) {
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all_data[[counter]] <- generate_basis_data(5, m, s, nc, tw, 2)
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counter <- counter + 1
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}
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}
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}
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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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