plot_1d {adaptMT} | R Documentation

## Plotting Functions for AdaPT with 1D Covariates

### Description

Plotting the outputs of `adapt` when `x` is 1-dimensional, including threshold curves and level curves of local FDR.

### Usage

    plot_1d_thresh(obj, x, pvals, alpha, title, xlab = "x", xlim = NULL,
      disp_ymax = 0.2, num_yticks = 3, rand_seed_perturb = NA, ...)

    plot_1d_lfdr(obj, x, pvals, alpha, title, xlab = "x", xlim = NULL,
      disp_ymax = 0.2, num_yticks = 3, legend_pos = "topright", ...)

### Arguments

`obj` | an 'adapt' object
`x` | covariates (i.e. side-information). Should be compatible to `models` and 1-dimensional.
`pvals` | a vector of values in [0, 1]. P-values
`alpha` | a positive scalar in (0, 1). Target FDR level
`title` | a string. Title of the figure
`xlab` | a string. Label of the x-axis
`xlim` | a vector of length 2. Limits of x-axis
`disp_ymax` | a positive scalar in (0, 1]. Maximum value displayed in the y-axis
`num_yticks` | a positive integer. Number of ticks in the y-axis
`rand_seed_perturb` | random seed if jitter is added. NA if no jittering is needed
`...` | other arguments passed to `par`
`legend_pos` | a string. Position of the legend

### Examples

    # Load estrogen data
    data(estrogen)
    pvals <- as.numeric(estrogen$pvals)
    x <- data.frame(x = as.numeric(estrogen$ord_high))
    dist <- beta_family()

    # Subsample the data for convenience
    inds <- (x$x <= 5000)
    pvals <- pvals[inds]
    x <- x[inds,,drop = FALSE]

    # Run adapt_glm
    library("splines")
    formulas <- paste0("ns(x, df = ", 6:10, ")")
    res <- adapt_glm(x = x, pvals = pvals, pi_formulas = formulas,
                     mu_formulas = formulas, dist = dist, nfits = 10)

    # Plots
    par(mfrow = c(2, 1))
    plot_1d_thresh(res, x, pvals, 0.1, "P-value Thresholds (alpha = 0.1)",
                   disp_ymax = 0.5)
    plot_1d_lfdr(res, x, pvals, 0.1, "Level Curves of lfdr (alpha = 0.1)",
                 disp_ymax = 0.5)

[Package adaptMT version 1.0.0 Index]