autoplot.auto_edina: Graph the Auto EDINA Object

In edina: Bayesian Estimation of an Exploratory Deterministic Input, Noisy and Gate Model

Description

Presents either the fitting of model heuristics or the evolution of parameters on a graph

Usage

## S3 method for class 'auto_edina'
autoplot(
  object,
  type = c("selection", "guessing", "slipping", "evolution"),
  ...
)

Arguments

object	An auto_edina object.
type	Kind of graph to display. Valid types: "selection" or "evolution".
...	Not used.

Value

A ggplot2 object.

See Also

auto_edina(), best_model(), model_selection_graph(), parameter_evolution_graph()

Examples

if(requireNamespace("simcdm", quietly = TRUE)) {

# Set a seed for reproducibility
set.seed(1512)

# Setup data simulation parameters
N = 2    # Number of Examinees / Subjects
J = 10   # Number of Items
K = 2    # Number of Skills / Attributes

# Note:
# Sample size and attributes have been reduced to create a minimally
# viable example that can be run during CRAN's automatic check.
# Please make sure to have a larger sample size...

# Assign slipping and guessing values for each item
ss = gs = rep(.2, J)

# Simulate an identifiable Q matrix
Q = simcdm::sim_q_matrix(J, K)

# Simulate subject attributes
subject_alphas = simcdm::sim_subject_attributes(N, K)

# Simulate items under the DINA model
items_dina = simcdm::sim_dina_items(subject_alphas, Q, ss, gs)


# Requires at least 15 seconds of execution time.
# Three EDINA models will be fit with increasing number of attributes.
model_set_edina = auto_edina(items_dina, k = 2:4)

# Visualize results results
autoplot(model_set_edina, type = "selection")

# Equivalent to:
model_selection_graph(model_set_edina)

# View model parameters
autoplot(model_set_edina, type = "guessing")

# Or directly call with:
parameter_evolution_graph(model_set_edina, type = "guessing")

}

edina documentation built on March 26, 2020, 9:30 p.m.