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Expressions for the fitting parameters (variances and covariance matrix) are derived, which are further used for the estimation of uncertainties.
Genetic parameters variances (phenotypic, genetic, environmental, phenotypic coefficient, genotypic coefficient, environmental coefficient, and broad-sense heritability) were estimated for each trait, separately and according to their approved lines, as well as the relative economic value of each trait involved in the design of the selection index equation.
In all final models for aphid population parameters, variances did not significantly differ between groups (Levene's test, P>0.05).
Each study was modelled separately and then the Wald statistics were calculated by combining the two sets of estimated parameters, variances and covariances.
Recently, Dominici et al. (2002b) identified that the application of GAM models in the S-Plus software (MathSoft, Inc., Cambridge, MA, USA) with the default convergence criteria leads to biased parameters' estimates, whereas Ramsay et al. (2003) found in addition that this function underestimated the parameters' variances.
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We simulate the sedimentation and fluidization of polydisperse suspensions and study the effects of two additional parameters: variance and autocorrelation decay rate of particle velocities.
We excluded variance in frequency modulation because of high inter-correlation (i.e. r>0.8) with other parameters (variance in frequency modulation – variance in amplitude modulation, r = 0.87; variance in frequency modulation – mean frequency modulation, r = 0.85) [28].
The variances were tested for heteroscedasticity and, for most parameters, variance was found to be heterogeneous.
In this respect the following parameters were estimated: PK parameters, variance and covariance of each individual specific parameter value and variance of the residual error.
Also, to avoid the underestimation of parameters variance, we used R Programming Environment for Data Analysis and Graphics (R Development Core Team 2004).
Parameter variances can be decreased by a factor of two by simply sampling at optimal times during the experiment.
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