Coverage excess from central quantiles at a zero-duration atom is the additional distributional probability included when a closed quantile interval captures an entire point mass at zero. Here coverage means probability under the stated duration model. For with , the zero mass is and the positive part is continuous. Let , , and use the lower quantiles from quantiles of a clipped Gaussian acquisition duration.
For the closed central interval , its probability isTo verify this, write the probability as . When both endpoints are positive, the lower left limit is and the upper value is . Once the lower endpoint is zero, its left limit is zero; if the upper endpoint is zero too, the interval contains exactly the zero atom. Endpoint inclusion is therefore part of the probability calculation.
For a nominal 95 percent central construction, zero masses , and give actual probabilities , and respectively. In the middle case, the excess is , not the whole atom: the interval already includes the probability between zero and the upper quantile.
As an original dimensional example, set , and , giving . The nominal central 95 percent interval is approximately and contains probability . SciPy documents the normal cdf and inverse-cdf ppf used to evaluate these Gaussian-component values.[ref]
SciPy 1.16.2 documentation. scipy.stats.norm, Methods: cdf and ppf
A one-sided upper interval or a separately specified probability construction can target a different included probability. Randomized endpoint inclusion at a zero-duration atom would require an explicit randomization rule, not a change made silently after seeing an endpoint equal zero. NIST explains why interval interpretation requires the input distributions and the chosen construction.[ref]
Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results by Barry N. Taylor and Chris E. Kuyatt. §6.3, Expanded Uncertainty
Distributional probability for this conditional acquisition model is separate from a worst-case optical-energy guarantee or a confidence procedure for an unknown fixed parameter.Gaussian input uncertainty at a clipped acquisition-time threshold produces a mixed output distribution rather than an ordinary Gaussian error bar. Hold the decay time fixed and assume the logarithmic input ratio has distribution , with . The required extension isThe directional derivative of a clipped logarithmic acquisition time explains the kink; here the full input distribution is propagated through it.
Writing and for the standard normal cumulative distribution function and density, respectively,For the continuous part has density . It integrates to less than one because the remaining probability is an atom at zero. Treating this density alone as the entire distribution loses that atom.
At the nominal threshold , half the outcomes are zero and the conditional positive part has a half-normal distribution. Direct integration of the normal density givesFor an original example, and logarithmic standard deviation give mean extension about and standard deviation , although inserting the nominal input into the clipped formula gives zero. The probability of an extension above is .
The quantiles of a clipped Gaussian acquisition duration must likewise include the zero atom. A symmetric interval around the nominal zero duration cannot represent these probabilities. NIST's uncertainty discussion stresses the need to know and combine input distributions when assigning an interval probability.[ref]
This is a stated uncertainty model for a conditional recording requirement, not a worst-case optical-energy guarantee. Uncertain decay time, correlation among the original envelope parameters or a non-Gaussian logarithmic ratio requires the corresponding joint propagation instead. Establishing the optical envelope remains a separate experimental task.