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发布于:2019-1-1 03:03:02  访问:13 次 回复:0 篇
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Un-Answered Questions Of Quisinostat Revealed
It also increases as skewness decreases (i.e. the proportion of longer CR histories increases). Consequently, scenario 2 (in which all individuals survive well, and detection is heterogeneous) was the most informative. Scenario 4 (in which detection is relatively high, and survival is heterogeneous) and scenario 3 (in which detection is relatively low and survival is heterogeneous) were less informative. Scenario Sirolimus datasheet 1 (in which all individuals have a reduced survival, and detection is heterogeneous) was the least informative. For each of these scenarios, situations with a negative skewness (i.e. a large proportion

of the population has a high detection probability) were the

most informative. To illustrate these differences among scenarios, we calculated the percentage of errors of classification (the number of individuals assigned to the wrong component, over the total number of individuals) using the estimated posterior probabilities that each individual belong to each component of the model involved in the calculation of the entropy (see Material and methods section). In a situation with ��?=?0.84, ��?=?0 and ��?=?0.5, the error rate was 12.9% in scenario 2, 14.6% in scenario 3, 14.3% in scenario 4 and 23.9% in scenario 1. As expected, in all scenarios, the error rate increased with ��, and decreased with �� and

�� (results not shown). All three criteria tended to select more complex models as the amount of information increased, but to a different level depending on their penalty. AIC has the least severe penalty (2k), so it rarely selected the 1-class model, selected the 2-class model when the amount of information was reduced (scenario 1, and scenario 3 and 4 with ��??0.5). The BIC penalty term is larger [k ln(n)], so it was more conservative than AIC, but performed less well than AIC when the amount of information was reduced as it selected the 1-class model more often (scenario 1), and better than AIC when the amount of information increased as it selected the 2-class model more often (scenario 3 and 4 with ��?>?0.5, and scenario 2 with ��?
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