leverage-hat

At its defaults it draws leverage and the deleted residual for 40 observations of a 6-column fit. The upper panel is the diagonal of the hat matrix, one bar per observation, with the average p/m = 0.150 drawn through it; the leverages sum to 6.000000000, which is exactly the number of columns. The lower panel is the leave-one-out residual, computed in closed form as eᵢ/(1 − hᵢ) and, separately, by refitting the model 40 times without each observation; the two agree to 1.3·10⁻¹². The first observation carries a leverage of 0.5000 by construction, and 1 − h is the number a hyperbolic downdate takes the square root of.

leverage-hat is one function in lib/figures/update.js — rank-one — the correction that is cheaper than the problem, and what it charges. Everything below came out of it during this build, at arguments taken from the essays rather than invented for this page. A figure here is the figure a reader meets in an essay, and if the generator changes, this page changes with it.

The upper panel is the diagonal of the hat matrix, one bar per observation, with the average p/m = 0.150 drawn through it; the leverages sum to 6.000000000, which is exactly the number of columns. The lower panel is the leave-one-out residual, computed in closed form as eᵢ/(1 − hᵢ) and, separately, by refitting the model 40 times without each observation; the two agree to 1.3·10⁻¹². The first observation carries a leverage of 0.5000 by construction, and 1 − h is the number a hyperbolic downdate takes the square root of.

The upper panel is the diagonal of the hat matrix, one bar per observation, with the average p/m = 0.150 drawn through it; the leverages sum to 6.000000000, which is exactly the number of columns. The lower panel is the leave-one-out residual, computed in closed form as eᵢ/(1 − hᵢ) and, separately, by refitting the model 40 times without each observation; the two agree to 1.3·10⁻¹². The first observation carries a leverage of 0.5000 by construction, and 1 − h is the number a hyperbolic downdate takes the square root of.

The upper panel is the diagonal of the hat matrix, one bar per observation, with the average p/m = 0.200 drawn through it; the leverages sum to 8.000000000, which is exactly the number of columns. The lower panel is the leave-one-out residual, computed in closed form as eᵢ/(1 − hᵢ) and, separately, by refitting the model 40 times without each observation; the two agree to 4·10⁻¹³. The first observation carries a leverage of 0.5000 by construction, and 1 − h is the number a hyperbolic downdate takes the square root of.

Every figure above asserted its own claims on the way to being drawn, and a claim that failed would have failed the build rather than drawn a wrong picture. Those assertions used to leave no trace at all: a passing one returned true and the only evidence the figure had checked anything was that nothing crashed. The list below is what they actually said, collected by running this generator with an observer installed — not a description of what it is believed to check.

6 distinct claims across 3 sets of arguments, grouped below by shape — because most of them are one sentence with a different number in it, and how many separate times that sentence was put to the test is the informative part.

The rule does not apply to it. It factorises nothing, so there is no residual it could be withholding. That is worth stating rather than leaving blank: a site that reported the rule as satisfied by every generator would be counting mostly generators the rule never reached.

Across the library: the rule bites on 92 of 198 generators — 77 print a residual and 15 are exempt with a published reason; 106 factorise nothing. Read from lib/residual-rule.js, which is the same body the gate enforces from, and the gate's last check fails the build if this page and it disagree about any generator.