/**
 * Shared mathematical functions for statistical calculations.
 *
 * These functions were previously duplicated across multiple domain files.
 * Consolidated here for maintainability.
 */
/**
 * Interval propagation through an arbitrary function by corner-case
 * evaluation: run `fn` at every combination of each uncertain input's
 * ± half-width, and take the min/max of the extracted output over those
 * corners plus the nominal point.
 *
 * No Monte Carlo, no distribution -- a caller who wants a defensible range
 * from a measurement uncertainty (an instrument's stated accuracy, not a
 * probability model) gets exactly that. Exact for a function monotonic in
 * each uncertain input; a sound bound for a smooth one over a small
 * uncertainty window even where the sign of a partial derivative varies
 * elsewhere in the input space (as it does for `kFactorReverse` across
 * different bend angles) -- the window itself is small enough that the
 * function's local behavior around the nominal point is what matters, not
 * its global shape.
 *
 * `2^n` evaluations for `n` uncertain inputs -- deliberately only for small
 * `n` (a handful of measured quantities feeding one derived value), not a
 * general sensitivity-analysis tool.
 *
 * @param nominal - the input at its stated (measured) values
 * @param uncertainty - a ± half-width for each input that carries one;
 *   inputs not listed here are treated as exact
 * @param fn - the function to propagate through
 * @param pick - extracts the single numeric output to bound from `fn`'s result
 */
export declare function propagate<TIn extends object, TOut>(nominal: TIn, uncertainty: Partial<Record<keyof TIn, number>>, fn: (input: TIn) => TOut, pick: (output: TOut) => number): {
    value: number;
    min: number;
    max: number;
};
/**
 * Standard normal CDF approximation using Abramowitz and Stegun.
 *
 * @param x - z-score
 * @returns Cumulative probability P(Z ≤ x)
 */
export declare function normalCDF(x: number): number;
/**
 * Approximation of the inverse normal CDF (probit function).
 * Uses rational approximation from Abramowitz and Stegun.
 *
 * @param p - Probability (0 < p < 1)
 * @returns z-score such that P(Z ≤ z) = p
 */
export declare function normalInvCDF(p: number): number;
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