metric_element_wise: Metric for Element-Wise Accuracy
In tmsalab/edmcore: Algorithms used across Exploratory Diagnostic Modeling

Description Usage Arguments Details Value Recovery Use See Also Examples

Computes the element-wise accuracy of matrices.

1	metric_element_wise(estimate, oracle, na.rm = FALSE)

`estimate`	Estimated values from the model.
`oracle`	Known values used to generate the model.
`na.rm`	A `logical` indicating if missing values (including NaN) should be removed. Default: `FALSE`

The element-wise metric is also known as accuracy or the proportion of estimated values that are equivalent to the same elements in the oracle value.

The metric is computed under:

\frac{1}{JK}∑ _{j=1}^J∑ _{k=1}^K\mathcal I(\hat{θ}_{jk}=θ_{jk})

A single numeric value between 0 and 1.

The element-wise recovery metric is best used to understand differences between dichotomous matrices such as the \boldsymbol{Q} and \boldsymbol{Δ} matrices.

base::norm()

# Construct data
estimate = matrix(c(1,1,2,4,3,6), nrow = 2, ncol = 3)
truth = matrix(c(1,2,3,4,5,6), nrow = 2, ncol = 3)

# Compute the frobenius norm
metric_element_wise(estimate, truth)