amse: Average root mean square error

In sgr: Sample Generation by Replacement

Average root mean square error

Description

Average root mean square error (AMSE).

Usage

amse(Bpar, B0)

Arguments

Bpar	Matrix with dimension B (replicates) \times P (parameters).
B0	Vector of true parameter values.

Details

Let \hat{θ}_{ij} be the estimated parameter value for the jth parameter in the ith sample (replicate), i = 1, 2, … B, j = 1, 2, … P, and let θ_{j} be the corresponding true parameter value, the Average root mean square error is defined as follows:

AMSE=\frac{1}{B}∑_{i}√{\frac{1}{P} ∑_{j} ≤ft[ \frac{\hat{θ}_{ij}-θ_{j}}{θ_{j}} \right]^2}

Value

Gives the AMSE value.

Note

If θ_{j} = 0, the ratio ≤ft[ \frac{\hat{θ}_{ij}-θ_{j}}{θ_{j}} \right] is modified as follows: ≤ft[ \frac{\hat{θ}_{ij}-0}{1} \right]

Author(s)

Massimiliano Pastore & Luigi Lombardi

References

Yang-Wallentin, F., Joreskog, K. G., Luo, H. (2010). Confirmatory Factor Analysis of Ordinal Variables With Misspecified Models, Structural Equation Modeling: A Multidisciplinary Journal, 17, 392-423.

See Also

arb

sgr documentation built on April 14, 2022, 5:08 p.m.