Exact(5)
IVS coordinates the observations, the data flow, the correlation, the data analysis and the technology developments.
Although this is a meaningful correlation, the data indicate that other factors besides lignin concentration have an exacerbating effect on recalcitrance, as supported by the individual analysis of stem and leaf data.
To estimate an approximated phenotypic correlation, the data were restructured and reduced to adjacent pairs of bacteria negative and positive SCS data, i.e. the bacteria negative and positive SCS observations closest within one lactation were used.
For the progeny lines with a significant marker-trait correlation, the data were also used to estimate additive and dominance effects of the QTL/gene using the model, (Model2) y i k = μ + a x + d z + ε i k Model (2) was modified from model (1) by removing variables related to the second locus.
To challenge this correlation, the data were split into a training and a test set, which produced an R for the test set of 0.61 (Fig. S1 †), confirming on comparison of the R in Fig. 2 that this correlation was not a product of over fitting.
Similar(55)
In our case, due to the size of the data set, we use a 5-fold cross-correlation: the data set is broken in five sets, each containing five images.
Prior to calculating correlations the data were filtered to remove non-varying genes.
Ebisuzaki, W. A method to estimate the statistical significance of a correlation when the data are serially correlated.
Spearman's rank correlation coefficient will only identify the strength of correlation where the data is consistently increasing or decreasing.
The main assumption of this work was to ignore the correlation between the data vector and the weights and compare the correlation between data vectors, preserving past and present data vector correlations.
The correlation of the data at the two time points was calculated using Pearson's correlation coefficient.
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