amse | R Documentation |
Average root mean square error (AMSE).
amse(Bpar, B0)
Bpar |
Matrix with dimension B (replicates) \times P (parameters). |
B0 |
Vector of true parameter values. |
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}
Gives the AMSE value.
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]
Massimiliano Pastore & Luigi Lombardi
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.
arb
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