Model - Stat functions
Every function callable as Stat.* inside an expression — an argument input, a parameter binding, a table cell. Pure: no side effects, no async.
| Function | Returns | Description | Arg | Type | Meaning |
|---|---|---|---|---|---|
Stat.fitLine(xs, ys) | fit | Ordinary least-squares linear regression: y = slope·x + intercept, plus r². NaN triple for fewer than 2 paired points or a vertical (zero x-spread) scatter. | xs | number[] | x values |
ys | number[] | y values, zipped to the shorter length | |||
Stat.max(values) | number | Largest value. NaN for an empty array. | values | number[] | the numbers |
Stat.mean(values) | number | Arithmetic mean. NaN for an empty array. | values | number[] | the numbers |
Stat.median(values) | number | Median (average of the two middle values on an even count). NaN for an empty array. | values | number[] | the numbers |
Stat.min(values) | number | Smallest value. NaN for an empty array. | values | number[] | the numbers |
Stat.percentile(values, p) | number | Linear-interpolation percentile — p=0 is min, p=100 is max, p=50 matches median. NaN for an empty array. | values | number[] | the numbers |
p | number | percentile 0..100 (clamped), linear interpolation between ranks | |||
Stat.std(values) | number | Sample standard deviation (√variance, n−1 denominator). NaN for fewer than 2 values. | values | number[] | the numbers |
Stat.sum(values) | number | Sum of the values. 0 for an empty array. | values | number[] | the numbers |
Stat.variance(values) | number | Sample variance (n−1 denominator, Bessel's correction). NaN for fewer than 2 values. | values | number[] | the numbers |