center.test {familial} | R Documentation |
Center test
Description
Performs a one- or two-sample test for a family of centers.
Usage
center.test(
x,
y = NULL,
family = "huber",
alternative = c("two.sided", "less", "greater"),
mu = 0,
paired = FALSE,
nboot = 1000,
loss = NULL,
cluster = NULL,
...
)
Arguments
x |
a numeric vector of data |
y |
an optional numeric vector of data |
family |
the family of centers; currently only allows 'huber' for Huber family |
alternative |
the form of the alternative hypothesis; must be one of 'two.sided' (default), 'greater', or 'less' |
mu |
the null value of the center for a one-sample test, or the null value of the center of differences for a paired two-sample test, or the null value of the difference of centers for an independent two-sample test; can be an interval |
paired |
a logical indicating whether to treat |
nboot |
the number of bootstraps to perform |
loss |
an optional c×2 matrix of losses incurred from an incorrect decision, where c is the number of candidate choices (typically c=3: H0, H1, or indeterminate) |
cluster |
an optional cluster for running bootstraps in parallel; must be set up using
|
... |
any other arguments |
Details
Uses the Bayesian bootstrap to compute posterior probabilities for the hypotheses
\mathrm{H}_0:\mu(\lambda)=\mu_0
for some \lambda\in\Lambda
vs.
\mathrm{H}_1:\mu(\lambda)\neq\mu_0
for all \lambda\in\Lambda
,
where \{\mu(\lambda):\lambda\in\Lambda\}
is a family of centers.
The default loss matrix results in a decision whenever the posterior probability
for one of the hypotheses is greater than 0.95 and otherwise is indeterminate.
Value
An object of class center.test
; a list with the following components:
expected.loss |
the expected loss, calculated by post-multiplying |
decision |
the optimal decision given the expected loss |
loss |
the loss matrix |
prob |
the estimated posterior probabilities of the null and alternative |
boot |
the bootstrap output from |
x |
the |
y |
the |
mu |
the |
family |
the |
Author(s)
Ryan Thompson <ryan.thompson1@unsw.edu.au>
References
Thompson, R., Forbes, C. S., MacEachern, S. N., and Peruggia, M. (2023). 'Familial inference: Tests for hypotheses on a family of centres'. arXiv: 2202.12540.
Examples
set.seed(123)
test <- center.test(MASS::galaxies, mu = 21000, nboot = 100)
print(test)
plot(test)
cl <- parallel::makeCluster(2)
test <- center.test(MASS::galaxies, mu = 21000, nboot = 100, cluster = cl)
parallel::stopCluster(cl)
print(test)