The function selects from a set of points along the range of x values these points that are close to a certain quantile of y. First, x values are classified in n groups. Secondly, the specified quantile of y is computed for each group. Thirdly, all y values in a group that are outside +- 0.05 of the estimated quantile are removed. See examples for an illustration.

1 | ```
SelectQuantiles(x, y, q = 0.5, n = NULL, ...)
``` |

`x` |
vector of x values |

`y` |
vector of y values |

`q` |
quantile value for which data should be selected |

`n` |
number of classes for x |

`...` |
further arguments |

Matthias Forkel <matthias.forkel@geo.tuwien.ac.at> [aut, cre]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
# x and y points
x <- 1:1000
y <- x * rnorm(1000, 1, 3)
plot(x, y)
# select points that are close to the median
q05 <- SelectQuantiles(x, y)
points(q05$x, q05$y, col="red")
# select points that are close to the 0.9 quantile
q09 <- SelectQuantiles(x, y, 0.9)
points(q09$x, q09$y, col="blue")
# select points that are close to the 0.1 quantile
q01 <- SelectQuantiles(x, y, 0.1)
points(q01$x, q01$y, col="purple")
# the selected points can be used for fits to a specific quantile
abline(lm(y ~ x, q09), col="blue")
abline(lm(y ~ x, q01), col="purple")
``` |

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