Calculate the difference between the empirical (S) and the model-implied indicator variance-covariance matrix (Sigma_hat) using different distance measures.

calculateDG(
.object = NULL,
.matrix1 = NULL,
.matrix2 = NULL,
.saturated = FALSE,
...
)

calculateDL(
.object = NULL,
.matrix1 = NULL,
.matrix2 = NULL,
.saturated = FALSE,
...
)

calculateDML(
.object = NULL,
.matrix1 = NULL,
.matrix2 = NULL,
.saturated = FALSE,
...
)

## Arguments

.object

An R object of class cSEMResults resulting from a call to csem().

.matrix1

A matrix to compare.

.matrix2

A matrix to compare.

.saturated

Logical. Should a saturated structural model be used? Defaults to FALSE.

...

Ignored.

## Value

A single numeric value giving the distance between two matrices.

## Details

The distances may also be computed for any two matrices A and B by supplying A and B directly via the .matrix1 and .matrix2 arguments. If A and B are supplied .object is ignored.

## Functions

• calculateDG: The geodesic distance (dG).

• calculateDL: The squared Euclidean distance

• calculateDML: The distance measure (fit function) used by ML