<p>The mean squared errors were obtained from 100 replicated simulations. The overall proportion of the phenotypic variance contributed by all simulated QTL was calculated using . Each panel contains the result of five different sample sizes (<i>n</i>). The phenotypic variance of the simulated trait is indicated by the dashed horizontal line in each panel (each panel represents one of the four different scenarios).</p
It is demonstrated how to select error mean squares for setting confidence intervals and testing for...
a<p>Lowest values of .</p><p>Mean and standard deviation of for the phenotype for different values...
Data of binary traits with different incidences were simulated: 5%, 15% and 50%. Other parameters: N...
<p>The mean squared errors were obtained from 100 replicated simulations. The overall proportion of ...
<p>The mean squared errors were obtained from 100 replicated simulations. The overall proportion of ...
<p>The filled circles indicate the MSE under the infinitesimal model while the open circles indicate...
<p>Left panel: distribution of 200 effects within each of 4 bootstrap samples (1–4), and within the ...
<p>The first three columns are the averaged standard error observed from 100 simulations under three...
<p>Averaged over 100 simulated data in <i>Scenario</i> 1 for two set of gene effect sizes . The top ...
<p>Left panel: variance (VAR) among 500 GBLUPs in each of 500 bootstrap samples. The horizontal line...
The objective of this simulation study was to compare the effect of the number of QTL and distributi...
<p>The squared roots of the mean squared errors (RMSE) of the MLEs are given in parentheses.</p><p>T...
<p>Scenarios differed in training data size, number of chromosomes, number of QTL, and whether the g...
<p><b>) for all-pairs (left) and Marcus-type (right) comparisons using normal (upper row) and log-no...
Data of binary traits with different incidences were simulated: 5%, 15% and 50%. Other parameters: N...
It is demonstrated how to select error mean squares for setting confidence intervals and testing for...
a<p>Lowest values of .</p><p>Mean and standard deviation of for the phenotype for different values...
Data of binary traits with different incidences were simulated: 5%, 15% and 50%. Other parameters: N...
<p>The mean squared errors were obtained from 100 replicated simulations. The overall proportion of ...
<p>The mean squared errors were obtained from 100 replicated simulations. The overall proportion of ...
<p>The filled circles indicate the MSE under the infinitesimal model while the open circles indicate...
<p>Left panel: distribution of 200 effects within each of 4 bootstrap samples (1–4), and within the ...
<p>The first three columns are the averaged standard error observed from 100 simulations under three...
<p>Averaged over 100 simulated data in <i>Scenario</i> 1 for two set of gene effect sizes . The top ...
<p>Left panel: variance (VAR) among 500 GBLUPs in each of 500 bootstrap samples. The horizontal line...
The objective of this simulation study was to compare the effect of the number of QTL and distributi...
<p>The squared roots of the mean squared errors (RMSE) of the MLEs are given in parentheses.</p><p>T...
<p>Scenarios differed in training data size, number of chromosomes, number of QTL, and whether the g...
<p><b>) for all-pairs (left) and Marcus-type (right) comparisons using normal (upper row) and log-no...
Data of binary traits with different incidences were simulated: 5%, 15% and 50%. Other parameters: N...
It is demonstrated how to select error mean squares for setting confidence intervals and testing for...
a<p>Lowest values of .</p><p>Mean and standard deviation of for the phenotype for different values...
Data of binary traits with different incidences were simulated: 5%, 15% and 50%. Other parameters: N...