parametric method वाक्य
उदाहरण वाक्य
मोबाइल
- This limits the ability of parametric methods to detect ancient HGTs.
- Another justification for the use of non-parametric methods is simplicity.
- For example parametric methods include multiple linear regression; non-parametric techniques include local smoothing.
- Also, due to the reliance on fewer assumptions, non-parametric methods are more robust.
- In terms of levels of measurement, non-parametric methods result in " ordinal " data.
- SSA can be effectively used as a non-parametric method of time series monitoring and change detection.
- To detect HGT using parametric methods, the host's genomic signature needs to be clearly recognizable.
- As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods.
- As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods.
- One can compute prediction intervals without any assumptions on the population; formally, this is a non-parametric method.
- For advanced methods such as higher-way ANOVA regression analysis, and mixed models, only exact parametric methods are available.
- In certain cases, even when the use of parametric methods is justified, non-parametric methods may be easier to use.
- In certain cases, even when the use of parametric methods is justified, non-parametric methods may be easier to use.
- For instance, the non-parametric method may produce very complicated responses to input variables that could include behavior that is not statistically significant.
- He was one of the creators of the non-parametric methods in mathematical statistics and of the theory of limit distributions of order statistics.
- The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences.
- Non-parametric methods are widely used for studying populations that take on a ranked order ( such as movie reviews receiving one to four stars ).
- The main feature of parametric methods is that they only rely on the genome under study to infer HGT events that may have occurred on its lineage.
- Due both to this simplicity and to their greater robustness, non-parametric methods are seen by some statisticians as leaving less room for improper use and misunderstanding.
- The major benefit of using non-parametric methods in a RDD is that they provide estimates based on data closer to the cut-off, which is intuitively appealing.
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