plot_covariance function

Plot Covariance between predictor (components) and response (components)

plot_covariance(
  sigma_df,
  lambda_df = NULL,
  base_theme = theme_grey,
  lab_list = NULL,
  theme_list = NULL
)

Arguments

• 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

Returns

A plot of true regression coefficients for the simulated data

Examples

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"
    )
)