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The stability parameters were: regression coefficient, variance due to regression and coefficient of determination.
Asymptotically Median Unbiased Estimation of Coefficient Variance in a Time Varying Parameter Model, (with James Stock), Journal of the American Statistical Association, vol. 93, No. 441, March 1998, pp 349-358.
By using the direct Liapunov method, bounds for the almost sure instability of beams as a function of viscous damping coefficient, variance of the stochastic force, ratio of principal lamina stiffnesses, shear correction factor, number of layers, mode numbers and geometrical ratio, are obtained.
In contrast, the coefficient variance changes from 0.198346 to 1.176139, almost 10 times that of the previous result.
In the present implementation, spatial noise is assumed homogeneous and normally distributed which implies a chi-squared distribution for wavelet coefficient variance.
Although the basic tendency was the same, i.e., a small coefficient variance was found by using feature regions with weight coefficient (g_j), the SIFT feature showed better performance compared with the proposed method.
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Survival coefficients in this discrete-time survival analyses model were converted to odds ratios (ORs) for ease of interpretation; significance tests of sets of coefficients in the logistic regression models were made using Wald X2 tests based on design-corrected coefficient variance-covariance matrices.
Multivariate significance was evaluated with Wald χ2 tests based on design-corrected coefficient variance-covariance matrices.
Multivariate significance was evaluated using the Wald test based on design corrected coefficient variance-covariance matrices.
Multivariate significance tests were made with Wald Chi-squared tests using Taylor series design-based coefficient variance-covariance matrices.
The intra- and inter-assay coefficient variances in the kit were < 5%.
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