F statistics which include FIT, deviations from Hardy- Weinberg expectation across the whole population, FIS deviation from Hardy- Weinberg expectation within a population and FST, correlation of alleles between subpopulation was calculated using AMOVA approach in Arlequin.
The method of fitting deviations of the measured values from the individual submodels by lower order associated Legendre polynomials has been employed to describe these temporal variations.
Open image in new window Fig. 2 The viscosity-torque curve at 400 r/min Table 3 The viscosity-torque correlations at 400 r/min Re Equation Correlation coefficient (R 2) Mean fit relative deviation Mean fit absolute deviation (mPa s) ≤36 (mu = 32222 M - 300.63) 0.9973 1.31 13.2 >36 (mu = 2 times 10^{7} times M^{2.8926}) 0.9990 3.73 7.0.
The mean fit relative deviation is no more than 3.73%, which has a good fitting result.
Here lack of fit means deviation of (model) predicted (m) frequencies from observed frequencies (n) [ 16].
As gam-5 requires less information than gam-6, it can be seen as a good compromise between an unbiased fit and deviation identification.
Let be the fitted value for the i-th individual at time t, where is the fitted mean response and is the fitted individual deviation at time t, using the BLUPs of the random effects,.
Although the data showed non-random oscillations around the linear fit, the deviations were small (the two largest deviations were a 5% error at δs = 115 μm and 6% error at δs = 385 μm).
If this is the case, circle of confusion estimates should be smaller when fitting to deviations calculated after the turtles crossed the Gulf Stream than for deviations calculated before the turtles crossed.
Multivariate curve resolution-alternating least squares (MCR-ALS) models were successfully developed to follow the fermentation progress (99.9% of explained variance, 3.5% lack of fit, and standard deviation of the residuals lower than 0.023).
