Plot Parameter Identifiability — plot

Creates a ranked lollipop plot of parameter identifiability based on the singular value decomposition of the Jacobian matrix. Accepts either a numeric Jacobian matrix in memory or a path to a .jco (PEST binary) file. High-dimensional problems are kept legible by showing only the most identifiable parameters (see top_n).

Usage

plot_identifiability(
  jacobian = NULL,
  jco_file = NULL,
  pst = NULL,
  n_sv = NULL,
  top_n = NULL,
  title = "Parameter Identifiability"
)

Arguments

jacobian: Numeric matrix (n_obs x n_par). The Jacobian / sensitivity matrix. Column names, if present, are used as parameter labels; otherwise p1, p2, ... are generated. Either jacobian or jco_file must be supplied.
jco_file: Character. Path to a .jco (Jacobian) binary file. Mutually exclusive with jacobian.
pst: A pesto_pst object supplying parameter names. Optional; used only when reading from a .jco file that carries no column names, in which case the labels are taken from its parameter table, positionally. Errors if its parameter count does not match the Jacobian's columns.
n_sv: Integer. Number of singular values to retain.
top_n: Integer. Maximum number of parameters to display, ranked by identifiability. Defaults to all parameters when there are at most 40 and to the 40 most identifiable otherwise, so high-dimensional problems stay legible. Set explicitly to override; a subtitle records how many of the total are shown.
title: Character. Plot title.

Value

A ggplot2 object.

Examples

J <- matrix(rnorm(30 * 8), nrow = 30, ncol = 8)
J[, 7] <- 0.5 * J[, 1] + 0.5 * J[, 2]
J[, 8] <- 1e-6 * rnorm(30)
colnames(J) <- paste0("k", 1:8)
p <- plot_identifiability(jacobian = J)
inherits(p, "ggplot")
#> [1] TRUE