| CTP_TMTI | R Documentation | 
A Closed Testing Procedure for the TMTI using an O(n^2) shortcut
CTP_TMTI(
  pvals,
  alpha = 0.05,
  B = 1000,
  gammaList = NULL,
  tau = NULL,
  K = NULL,
  is.sorted = FALSE,
  EarlyStop = FALSE,
  ...
)
TMTI_CTP(
  pvals,
  alpha = 0.05,
  B = 1000,
  gammaList = NULL,
  tau = NULL,
  K = NULL,
  is.sorted = FALSE,
  ...
)
| pvals | A vector of p-values. | 
| alpha | Level to perform each intersection test at. Defaults to 0.05. | 
| B | Number of bootstrap replications if gamma needs to be approximated. Not used if specifying a list of functions using the gammaList argument or if length(pvals) <= 100. Defaults to 1000. | 
| gammaList | A list of pre-specified gamma functions. If NULL, gamma functions will be approximated via bootstrap, assuming independence. Defaults to NULL. | 
| tau | Numerical (in (0,1)); threshold to use in tTMTI. If set to NULL, then either TMTI (default) or rtTMTI is used. | 
| K | Integer; Number of smallest p-values to use in rtTMTI. If se to NULL, then either TMTI (default) or tTMTI is used. | 
| is.sorted | Logical, indicating the p-values are pre-sorted. Defaults to FALSE. | 
| EarlyStop | Logical indicating whether to exit as soon as a non-significant p-value is found. Defaults to FALSE. | 
| ... | Additional arguments. | 
A data.frame containing adjusted p-values and the original index of the p-values.
## Simulate some p-values
## The first 10 are from false hypotheses, the next 10 are from true
pvals = c(
  rbeta(10, 1, 20), ## Mean value of .05
  runif(10)
)
CTP_TMTI(pvals)
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