(3) In this paper, the investigation of investment risk is based on interest rates and temporal and spatial population covariance
and variations of population distribution year by year.
We therefore use the following to determine the total covariance matrix, when the two population covariance
matrices are equivalent:
For several learning problems, estimates of the inverse population covariance
are required and often obtained by inverting the model covariance matrix.
According to Hu and Bentler (1998), the SRMR is most sensitive to misspecified factor covariances, while the RMSEA is an indication of a lack of fit of the model to the population covariance
It asks the question <<How well would the model, with unknown but optimally chosen parameter values, fit the population covariance
matrix if it were available?>> (Browne & Cudeck, 1993, pp.
A GFI of 0.99 indicates that 99% of the sample covariance matrix fits the population covariance
We test the hypothesis that the population covariance
of observed variables equals the covariance matrix implied by a particular model.
Chen's (1979) approach was to assume a given structural form for [Omega], the mean of the prior distribution of the population covariance
matrix [Sigma], and to estimate the posterior mode (or mean, as a result of symmetry), given the prior structural model.
The OMD estimator, [[Theta].sub.n, OMD], is obtained by setting [[Omega].sub.n] equal to the inverse of an estimator of the population covariance
matrix of [S.sub.n].
The estimates of the cumulative net selection gradients were greater for the assumption of a genetic architecture similar to the modern populations than for the assumption of a genetic architecture similar to the overall population covariance
matrix (Table 5).
Compared to two other variations, the hot-deck distance method performed better in retaining the population covariance
structure in imputed samples.
A non-significant [chi square] indicates that the model fits the data and that the model can reproduce the population covariance
matrix (Kelloway, 1998).