NRtest.object: S3 Class "NRtest"

In HDNRA: High-Dimensional Location Testing with Normal-Reference Approaches

S3 Class "NRtest"

Description

The "NRtest" objects provide a comprehensive summary of hypothesis test outcomes, including test statistics, p-values, parameter estimates, and confidence intervals, if applicable.

Usage

NRtest.object(
  statistic,
  p.value,
  method,
  null.value,
  alternative,
  parameter = NULL,
  sample.size = NULL,
  sample.dimension = NULL,
  estimation.method = NULL,
  data.name = NULL,
  ...
)

Arguments

statistic	Numeric scalar containing the value of the test statistic, with a names attribute indicating the name of the test statistic.
p.value	Numeric scalar containing the p-value for the test.
method	Character string giving the name of the test.
null.value	Character string indicating the null hypothesis.
alternative	Character string indicating the alternative hypothesis.
parameter	Numeric vector containing the estimated approximation parameter(s) associated with the approximation method. This vector has a names attribute describing its element(s).
sample.size	Numeric vector containing the number of observations in each group used for the hypothesis test.
sample.dimension	Numeric scalar containing the dimension of the dataset used for the hypothesis test.
estimation.method	Character string giving the name of the approximation approach used to approximate the null distribution of the test statistic.
data.name	Character string describing the data set used in the hypothesis test.
...	Additional optional arguments.

Details

A class of objects returned by high-dimensional hypothesis testing functions in the HDNRA package, designed to encapsulate detailed results from statistical hypothesis tests. These objects are structured similarly to htest objects in the package EnvStats but are tailored to the needs of the HDNRA package.

Value

An object of class "NRtest" containing both required and optional components depending on the specifics of the hypothesis test, shown as follows:

Required Components

These components must be present in every "NRtest" object:

statistic

Must e present.

p.value

Must e present.

null.value

Must e present.

alternative

Must e present.

method

Must e present.

Optional Components

These components are included depending on the specifics of the hypothesis test performed:

parameter

May be present.

sample.size

May be present.

sample.dimension

May be present.

estimation.method

May be present.

data.name

May be present.

Methods

The class has the following methods:

print.NRtest

Printing the contents of the NRtest object in a human-readable form.

Examples

# Example 1: Using Bai and Saranadasa (1996)'s test (two-sample problem)
NRtest.obj1 <- NRtest.object(
  statistic = c("T[BS]" = 2.208),
  p.value = 0.0136,
  method = "Bai and Saranadasa (1996)'s test",
  data.name = "group1 and group2",
  null.value = c("Difference between two mean vectors is o"),
  alternative = "Difference between two mean vectors is not 0",
  parameter = NULL,
  sample.size = c(n1 = 24, n2 = 26),
  sample.dimension = 20460,
  estimation.method = "Normal approximation"
)
print(NRtest.obj1)

# Example 2: Using Fujikoshi et al. (2004)'s test (GLHT problem)
NRtest.obj2 <- NRtest.object(
  statistic = c("T[FHW]" = 6.4015),
  p.value = 0,
  method = "Fujikoshi et al. (2004)'s test",
  data.name = "Y",
  null.value  = "The general linear hypothesis is true",
  alternative = "The general linear hypothesis is not true",
  parameter = NULL,
  sample.size = c(n1 = 43, n2 = 14, n3 = 21, n4 = 72),
  sample.dimension = 2000,
  estimation.method = "Normal approximation"
)
print(NRtest.obj2)

HDNRA documentation built on Oct. 30, 2024, 9:28 a.m.