Construct local confidence intervals for each parameter from the empirical joint distribution of a parameter vector of length P.

1 2 3 4 5 6 7 8 9 10 11 12 13 |

`x` |
an N-times-P matrix, or an object of class |

`conf.level` |
a single numeric value between 0.5 and 1, specifying the local confidence level for each of the P parameters |

`alternative` |
a single character string, one of |

`whichp` |
a single character string, naming an element of the |

`...` |
currently not used |

Construct simple confidence intervals based on order statistics applied to the marginal empirical distributions in `x`

.

An object of class "CInp", a list with elements

`conf.int ` |
a P-times-2 matrix containing the lower and upper confidence limits |

`estimate ` |
a numeric vector of length P, containing the medians of the P marginal empirical distributions |

`x ` |
the input object |

`k ` |
the number of values outside each confidence interval, i.e. conf.level*N |

`N ` |
the number of values used to construct each confidence interval |

`conf.level ` |
a single numeric value, the nominal confidence level, as input |

`alternative ` |
a single character string, as input |

The function internally used is `quantile`

with its default settings.
See `SCSnp`

for simultaneous sets.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
# Assume a 100 times 4 matrix of 4 mutually independent
# normal variables:
X<-cbind(rnorm(100), rnorm(100), rnorm(100), rnorm(100))
lcits<-CInp(x=X, conf.level=0.95, alternative="two.sided")
lcits
ci1<-lcits$conf.int[1,]
length( which(X[,1]>=ci1[1] & X[,1]<=ci1[2] ) )
ci2<-lcits$conf.int[2,]
length( which(X[,2]>=ci2[1] & X[,2]<=ci2[2] ) )
``` |

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