Lines Matching full:distribution
1 Notes about distribution tables from Nistnet
3 I. About the distribution tables
5 The table used for "synthesizing" the distribution is essentially a scaled,
6 translated, inverse to the cumulative distribution function.
8 Here's how to think about it: Let F() be the cumulative distribution
9 function for a probability distribution X. We'll assume we've scaled
26 distribution has the same approximate "shape" as X, simply by letting
28 To see this, it's enough to show that Y's cumulative distribution function,
41 II. How to create distribution tables (in theory)
45 pareto distribution is one example of this. In other cases, and
46 especially for matching an experimentally observed distribution, it's
48 a concrete example, namely how the new "experimental" distribution was
51 1. Collect enough data points to characterize the distribution. Here, I
58 3. Determine the cumulative distribution. The code I wrote creates a table
71 III. How to create distribution tables (in practice)
76 header file. So if you have your own time distribution, you can generate
