variable_ranking {RankPCA}

Calculate Variable Ranking

Description

This function calculates the ranking of variables based on the sum of absolute values for each row of loading vectors.

Usage

variable_ranking(loading_vectors)

Arguments

loading_vectors

A matrix containing loading vectors.

Value

A data frame containing the ranked variables.

Examples

# Define row and column names
row_names <- c("Category1A", "Category1B", "Category1C", "Category2X", "Category2Y",
               "Category2Z", "Category3M", "Category3N", "Category3O", "Continuous1",
               "Continuous2", "Continuous3", "Continuous4", "Continuous5")

col_names <- paste0("PC", 1:8)

# Define the data matrix
loading_vectors <- matrix(c(
  0.199, 0.268, 0.189, 0.641, 0.092, 0.171, 0.079, -0.070,
  0.244, -0.371, 0.042, -0.426, 0.358, -0.070, 0.016, 0.371,
  -0.435, 0.099, -0.227, -0.216, -0.441, -0.100, -0.094, -0.294,
  0.087, -0.338, 0.458, 0.083, -0.515, -0.150, 0.007, 0.029,
  -0.473, 0.170, -0.164, 0.172, 0.296, 0.006, -0.044, 0.462,
  0.407, 0.155, -0.279, -0.261, 0.198, 0.141, 0.039, -0.510,
  0.101, -0.487, -0.465, 0.302, -0.117, 0.062, 0.036, 0.035,
  0.145, 0.546, 0.057, -0.211, -0.123, -0.325, 0.287, 0.191,
  -0.274, -0.003, 0.491, -0.134, 0.271, 0.272, -0.349, -0.245,
  0.290, 0.207, 0.001, -0.048, -0.250, -0.090, -0.275, 0.330,
  -0.134, 0.099, -0.277, -0.072, -0.180, 0.485, 0.134, 0.147,
  0.006, 0.051, -0.216, 0.007, 0.008, -0.278, -0.712, 0.004,
  0.320, 0.145, -0.061, 0.146, -0.078, 0.215, -0.414, 0.096,
  0.061, 0.044, 0.096, -0.271, -0.273, 0.603, -0.064, 0.245
), ncol = 8, byrow = TRUE)

# Assign row and column names
rownames(loading_vectors) <- row_names
colnames(loading_vectors) <- col_names

# Now you can use the loading_vectors variable in your code
print(loading_vectors)
# rank the variables
ranked_variables <- variable_ranking(loading_vectors)
print(ranked_variables)