Quantiles of a test statistic
qStat.Rd
Quantile of a test statistic.
Usage
qStat(p, n,
type = c("Greenwood", "Jackson", "logLRGPD", "logLRLomax",
"logLRGEV", "logLRFrechet"),
outNorm = FALSE)
Arguments
- p
-
Numeric vector of probabilities. Very small values (
p < 0.01
) or very large ones (p > 0.99
) will be truncated as0.00
or1.00
to maintain a realistic level of precision. - n
-
Sample size.
- type
-
The type of statistic, see Details.
- outNorm
-
Logical. If
TRUE
the output is normalized in a such fashion that its distribution is the asymptotic one (i.e. standard normal in practice). WhenFALSE
, the quantiles are given in the true scale of the statistic: \(\textrm{CV}^2\), Jackson. For LR statistics this argument has no impact.
Details
The function provides an approximation of the distribution for several statistics.
For
"Greenwood"
, the statistic is Greenwood's statistic. The distribution is that of the squared coefficient of variation \(\textrm{CV}^2\) of a sample of sizen
from the exponential distribution as computed byCV2
.For
"Jackson"
, the statistic is Jackson's statistic, seeJackson
.For
"logLRGPD"
and"logLRLomax"
, the statistic is the log of the likelihood ratio of a sample from the exponential distribution. The log-likelihoods are for an exponential distribution compared to a GPD with non-zero shape, or to a GPD with positive shape (equivalently, a Lomax distribution).For
"logLRGEV"
and"logLRFrechet"
, the statistic is the log of the likelihood ratio of a sample from the Gumbel distribution. The log-likelihoods are for a Gumbel distribution compared to a GEV with non-zero shape, or to a GEV with positive shape (equivalently, a Fréchet distribution).
The log of Likelihood Ratios are multiplied by 2
, so that they
compare to a chi-square statistic with one degree of freedom.
Note
The precision of the result given is limited, and is about two-digits. This function is not intended to be used as such and is only provided for information.
Examples
res <- qStat(n = 40, type = "Greenwood")
#> Warning: 'p' contains values smaller than 0.005. Truncated.
#> Warning: 'p' contains values larger than 0.995. Truncated.
plot(res$q, res$p, type = "o")