Continuous real distribution function

On this page
  1. Mathematical statement
  2. Representative formula (exact TeX)
  3. Assumptions
  4. Symbol scope
  5. Intuition, definition, and misconceptions
  6. Adopted derivation guide
  7. Prerequisites
  8. Verification boundary
  9. Next obligation
  10. Same-source structured data

This English edition is an AI candidate and does not yet have an OCME Atlas (GPT-6) Twin closure receipt.

Here a continuous distribution means that its CDF is continuous; the CDF must still be nondecreasing, right-continuous and have endpoint limits0 and1.

mko-continuous-real-distribution-function · definition · v0.10.0

Mathematical statement

A continuous CDF has no jumps, so every singleton has probability0. This is not continuity of a random-variable map on the sample space and does not imply a density or absolute continuity. An affine Cantor distribution supplies a continuous, atomless, singular boundary. Flat CDF intervals are allowed; strict increase is not required.

Representative formula (exact TeX)

F(x)

Assumptions

  • Exact positive families use linear interpolation between knots, constant0 on the left and constant1 on the right.
  • Knot values are nondecreasing from0 to1, knots are strictly increasing, and audit query points must also be strictly ordered as exact rationals.

Symbol scope

  • F — continuous cumulative distribution function
  • x — real threshold

Intuition, definition, and misconceptions

CDF continuity is a property of the distribution.

Continuity implies zero point masses.

Continuity or atomlessness does not guarantee a density.

Do not identify a continuous CDF with existence of a PDF or demand strict increase.

Adopted derivation guide

A continuous CDF with a flat interval

The original MKO is retained. The guide has its own append-only revision and verification boundaries, not a new Lean proof.

Prerequisites

Verification boundary

Piecewise-linear families are exact instances; the singular boundary performs no density computation.

not_formalized

This does not mean the content is false; it means no replayable computational or formal evidence is registered yet.

Next obligation

Add the standard normal distribution.

Same-source structured data

This page and the interactive view use the same object and existing language edition; this adds no proof or human review.

Canonical MKO JSON · Plain Markdown