λ = 1
Table 1. Exponential cumulative distribution.
| CDF(X) |
| X Input |
P Output |
| 0 |
0 |
| 0.5 |
0.39346934028737 |
| 1 |
0.63212055882856 |
| 1.5 |
0.77686983985157 |
| 2 |
0.86466471676339 |
| 2.5 |
0.9179150013761 |
| 3 |
0.95021293163214 |
| 3.5 |
0.96980261657768 |
Table 2. Exponential inverse cumulative distribution.
| ICDF(P) |
| P Input |
X Output |
| 0 |
0 |
| 0.39346934028737 |
0.5 |
| 0.63212055882856 |
1 |
| 0.77686983985157 |
1.5 |
| 0.86466471676339 |
2 |
| 0.9179150013761 |
2.5 |
| 0.95021293163214 |
3 |
| 0.96980261657768 |
3.5 |
Table 3. Exponential variates generated using inverse cdf method.
| RNG via ICDF(U) |
| Counter |
Rnd Vals |
| 1 |
0.48559035479899 |
| 2 |
0.076816986340971 |
| 3 |
1.2611373303724 |
| 4 |
0.034180655859366 |
| 5 |
0.56248586920838 |
| 6 |
1.1390348634755 |
| 7 |
0.53030942435399 |
| 8 |
0.56312750305921 |
Table 4. Exponential variates generated using RNG method.
| RNG via RNG(N) |
| Counter |
Rnd Vals |
| 1 |
0.58112266083644 |
| 2 |
0.20185207653995 |
| 3 |
0.71731582287013 |
| 4 |
0.099821193815349 |
| 5 |
0.074475189101339 |
| 6 |
0.33964177759618 |
| 7 |
1.3847711660418 |
| 8 |
0.35347905126439 |
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