Description Usage Arguments Value Examples
View source: R/plotting-functions.R
Plot Covariance between predictor (components) and response (components)
1 2 3 4 5 6 7 | plot_covariance(
sigma_df,
lambda_df = NULL,
base_theme = theme_grey,
lab_list = NULL,
theme_list = NULL
)
|
sigma_df |
A data.frame generated by tidy_sigma |
lambda_df |
A data.frame generated by tidy_lambda |
base_theme |
Base ggplot theme to apply |
lab_list |
List of labs arguments such as x, y, title, subtitle |
theme_list |
List of theme arguments to apply in the plot |
A plot of true regression coefficients for the simulated data
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | sobj <- bisimrel(p = 12)
sigma_df <- sobj %>%
cov_mat(which = "zy") %>%
tidy_sigma() %>%
abs_sigma()
lambda_df <- sobj %>%
tidy_lambda()
plot_covariance(
sigma_df,
lambda_df,
base_theme = ggplot2::theme_bw,
lab_list = list(
title = "Covariance between Response and Predictor Components",
subtitle = "The bar represents the eigenvalues predictor covariance",
y = "Absolute covariance",
x = "Predictor Component",
color = "Response Component"
),
theme_list = list(
legend.position = "bottom"
)
)
|
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