CoverageObj-class: Class '"CoverageObj"'

In Blossom: Statistical Comparisons with Distance-Function Based Permutation Tests

Description

The CoverageObj class is used for the storage of coverage tests results.

Objects from the Class

Objects can be created by calls of the form new("CoverageObj", ...) or, more commonly, via the coverage function.

Slots

NumPerms:

The number of permutations used if a permutation test was performed.

DistExp:

The exponent used in calculation of distances.

NumGrps:

The number of groups in the input data.

GpSizes:

A vector of length NumGrps specifying group sizes.

inputData:

A data.frame used for the analysis. The first column is the group (if supplied) and the second is the variable for which the analysis was performed.

ObsDelta:

The observed coverage statistic.

VarDelta:

The variance of the coverage statistic estimated using resampling.

ExpectDelta:

The expected value of the coverage statistic.

DeltaSkew:

The standard deviation of the variance of the coverage statistic.

Z_value:

The observed standardized coverage statistic.

Skt:

The skewness of observed coverage statistic.

P_value:

The Pearson Type III probability of a larger or equal coverage statistic.

PZ:

The resampled probability of a larger or equal coverage statistic.

NumObs:

The total number of observations used in the analysis.

PermVals:

If save.test=TRUE was specified this vector will hold resampled test statistic values.

exact:

A logical value indicating whether an exact test was performed.

group.names:

The names of the groups used in the analysis.

Call:

The original function call.

Methods

print

signature(x = "CoverageObj"): Prints a terse summary of the Coverage test.

pvalue

signature(x = "CoverageObj"): Extracts the Pearson type III p-value. See pvalue.

ResampVals

signature(x = "CoverageObj"): Extracts the Monte Carlo resampled test statistic values. See ResampVals.

show

signature(object = "CoverageObj"): Same as print. See print.

summary

signature(object = "CoverageObj"): Prints a detailed summary of the Coverage test.

References

Mielke, P.W., and Y.C. Yao. 1988. A class of multiple sample tests based on empirical coverages. Annals of the Institute of Statistical Mathematics 40, 165–178.

Mielke, P.W. and Y.C. Yao. 1990. On g-sample empirical coverage tests: Exact and simulated null distributions of test statistics with small and moderate sample sizes. Journal Statistical Computation and Simulation 35, 31–39.

See Also

coverage

Examples

Out <- coverage(variable = bgrouse$distance,group = bgrouse$sex)
summary(Out)

Blossom documentation built on May 29, 2017, 10:55 p.m.