Description Usage Arguments Details Value Author(s) References See Also Examples

Computes the Harrell-Davis (1982) quantile estimator and jacknife standard errors of quantiles. The quantile estimator is a weighted linear combination or order statistics in which the order statistics used in traditional nonparametric quantile estimators are given the greatest weight. In small samples the H-D estimator is more efficient than traditional ones, and the two methods are asymptotically equivalent. The H-D estimator is the limit of a bootstrap average as the number of bootstrap resamples becomes infinitely large.

1 2 |

`x` |
a numeric vector |

`probs` |
vector of quantiles to compute |

`se` |
set to |

`na.rm` |
set to |

`names` |
set to |

`weights` |
set to |

A Fortran routine is used to compute the jackknife leave-out-one
quantile estimates. Standard errors are not computed for quantiles 0 or
1 (`NA`

s are returned).

A vector of quantiles. If `se=TRUE`

this vector will have an
attribute `se`

added to it, containing the standard errors. If
`weights=TRUE`

, also has a `"weights"`

attribute which is a matrix.

Frank Harrell

Harrell FE, Davis CE (1982): A new distribution-free quantile estimator. Biometrika 69:635-640.

Hutson AD, Ernst MD (2000): The exact bootstrap mean and variance of an L-estimator. J Roy Statist Soc B 62:89-94.

1 2 3 4 5 6 7 8 9 10 | ```
set.seed(1)
x <- runif(100)
hdquantile(x, (1:3)/4, se=TRUE)
## Not run:
# Compare jackknife standard errors with those from the bootstrap
library(boot)
boot(x, function(x,i) hdquantile(x[i], probs=(1:3)/4), R=400)
## End(Not run)
``` |

```
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2
Attaching package: 'Hmisc'
The following objects are masked from 'package:base':
format.pval, round.POSIXt, trunc.POSIXt, units
0.25 0.50 0.75
0.3064350 0.5054821 0.7571213
attr(,"se")
0.25 0.50 0.75
0.03931112 0.04878284 0.02997026
Attaching package: 'boot'
The following object is masked from 'package:survival':
aml
The following object is masked from 'package:lattice':
melanoma
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = x, statistic = function(x, i) hdquantile(x[i], probs = (1:3)/4),
R = 400)
Bootstrap Statistics :
original bias std. error
t1* 0.3064350 0.0006562956 0.03920786
t2* 0.5054821 0.0058713474 0.04745287
t3* 0.7571213 -0.0024634346 0.02804352
```

Hmisc documentation built on Jan. 4, 2018, 3:22 a.m.

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