nonparametric

Therefore, a nonparametric analysis was used to examine the complexity of the data.

The latter is a simple multiple of the nonparametric skew.

If the data is not normally distributed, nonparametric algorithms should be used.

In our example, we considered a nonparametric method to smooth sample variances.

Thus the estimation task is statistically harder in nonparametric models.

Currently, his main research interests are in nonparametric and high-dimensional statistics.

Many of his publications are related to rank-based nonparametric statistics.

An example is the Dirichlet process, which falls in the realm of nonparametric statistics.

It has been called "the most popular nonparametric technique for estimating a linear trend".

Any distribution for which this holds has either a zero or a positive nonparametric skew.

More recently, methods based on ideas from nonparametric statistics (which can be seen to construct their own features) have been explored.

The following table summarizes some common parametric and nonparametric tests for the means of one or more samples.

Therefore, we also used the nonparametric rank sum test, which is insensitive to a skewed distribution.

The Spearman correlation coefficient is often described as being "nonparametric".

Computer packages for using parametric and nonparametric kernel methods are available online.

K-S tests provide a nonparametric, sensitive and robust way to compare two distributions.

The nonparametric part is the unknown function .

In statistics, an additive model (AM) is a nonparametric regression method.

Replacing the denominator with the standard deviation we obtain the nonparametric skew.

"Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods".

For a discussion on choosing between the t and nonparametric alternatives, see Sawilowsky.

"Studies in certain types of nonparametric inference".

Its calculation does not require any knowledge of the form of the underlying distribution - hence the name nonparametric.

In contrast the nonparametric skew is -0.110.

The nonparametric skew does not satisfy these axioms.