| global.test {RecordTest} | R Documentation |
Global Statistic for Two-Sided Tests
Description
Performs a more powerful generalisation of the
two-sided tests in this package by means of the sum of the statistics of
upper and lower records in the forward and backward directions to study
the hypothesis of the classical record model (i.e., of IID continuous
RVs). The tests considered are the chi-square goodness-of-fit test
p.chisq.test, the regression test
p.regression.test,
the likelihood-ratio test lr.test, and the score test
score.test.
Usage
global.test(X, FUN, record = c(FU = 1, FL = 1, BU = 1, BL = 1), B = 1000, ...)
Arguments
X |
A numeric vector, matrix (or data frame). |
FUN |
One of the functions whose statistic is going to be used. One of
|
record |
Logical vector. Vector with four elements indicating if forward upper, forward lower, backward upper and backward lower are going to be shown, respectively. Logical values or 0,1 values are accepted. |
B |
An integer specifying the number of replicates used in the Monte Carlo approach. |
... |
Further arguments in the |
Details
The statistics, say X, of the tests p.chisq.test,
p.regression.test, lr.test or
score.test applied to the series of the forward upper,
forward lower, backward upper and backward lower records are summed to
develop a more powerful statistic:
X^{(FU)} + X^{(FL)} + X^{(BU)} + X^{(BL)}.
Other sums of statistics are allowed.
The distribution of this global statistics is unknown, but the p-value can be estimated with Monte Carlo simulations
Value
A list of class "htest" with the following elements:
statistic |
Value of the statistic. |
p.value |
Simulated p-value. |
method |
A character string indicating the type of test. |
data.name |
A character string giving the name of the data. |
Author(s)
Jorge Castillo-Mateo
See Also
p.chisq.test, p.regression.test,
lr.test, score.test
Examples
# not run because the simulations take a while if B > 1000
## global statistic with 4 types of record for p.chisq.test
#global.test(ZaragozaSeries, FUN = p.chisq.test)
## global statistic with 4 types of record for p.regression.test
#global.test(ZaragozaSeries, FUN = p.regression.test)
## global statistic with 4 types of record for score.test with restricted alternative
#global.test(ZaragozaSeries, FUN = score.test, probabilities = "equal")
## global statistic with 4 types of record for lr.test with restricted alternative
#global.test(ZaragozaSeries, FUN = lr.test, probabilities = "equal")
## global statistic with 2 types of 'almost' independent records for lr.test
#global.test(ZaragozaSeries, FUN = lr.test, record = c(1,0,0,1), probabilities = "different")