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What all these models have in common is that changes in g significantly affect the firing rate variance in the same direction, whereas x controls mainly the firing rate mean and has little or no effect on the variance.
On the other hand, the local entropy image can increase the contrast between the cytoplasmic and nuclear regions in some extent; however, the boundary of the transformed entropy images is quite blurred, and the intensity variance in the same regions of cellular components (cytoplasm/nucleus) is also large.
Parameters for traits measured under these circumstances are often cited as evidence of genetic variance in the same traits in wild populations.
Estimates of mutational variance from mutation accumulation studies are rarely matched with simultaneous estimates of the standing genetic variance in the same traits, measured under the same conditions (Houle et al. 1996).
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Since the trend and its slope are not stationary, it is not possible to estimate their variances in the same way.
The Haar-Fisz transformed data, no longer subject to the limitations of Poisson counting statistics, have a lower relative variance in those same regions.
Note that with the random effect of family (cross), we can either estimate one variance component (assuming the same variance in families over the four crosses) or four variance components (each one specific to each cross, assuming that the variances were heterogeneous).
The effective (minimum) number of genes (NE) for resistance to diclofop-methyl in parental, F1 and F2 families was estimated as suggested by Lande (1981) as: (1) μP2 – μP1 represent the difference in the mean phenotypic value (aboveground plant biomass) of parental populations (R and S) and σ 2 is the difference in variance for the same phenotypic trait between F2 and F1 families.
Any probability distribution with zero mean and the same variance will result in the same SINR.
This is indicated by the measurements of the channel capacity variance, also shown in the same figure plotted with reference to the right-hand y-axis.
Given that the tremor frequencies observed in the two pathologies overlap and tremor frequency variance is the same in the two pathologies (O'Suilleabhain and Matsumoto, 1998; Jankovic and Tolosa, 2007), the circuitry sustaining essential tremor must be more strongly coupled and prescriptive in the relative timing of neural activity between elements, necessary for sustaining essential tremor.
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