repl.txt (2019B)
1 2 {{alias}}( x, r, p ) 3 Evaluates the cumulative distribution function (CDF) for a negative binomial 4 distribution with number of successes until experiment is stopped `r` and 5 success probability `p` at a value `x`. 6 7 If provided `NaN` as any argument, the function returns `NaN`. 8 9 If provided a `r` which is not a positive number, the function returns 10 `NaN`. 11 12 If provided a success probability `p` outside of `[0,1]`, the function 13 returns `NaN`. 14 15 Parameters 16 ---------- 17 x: number 18 Input value. 19 20 r: number 21 Number of successes until experiment is stopped. 22 23 p: number 24 Success probability. 25 26 Returns 27 ------- 28 out: number 29 Evaluated CDF. 30 31 Examples 32 -------- 33 > var y = {{alias}}( 5.0, 20.0, 0.8 ) 34 ~0.617 35 > y = {{alias}}( 21.0, 20.0, 0.5 ) 36 ~0.622 37 > y = {{alias}}( 5.0, 10.0, 0.4 ) 38 ~0.034 39 > y = {{alias}}( 0.0, 10.0, 0.9 ) 40 ~0.349 41 > y = {{alias}}( 21.0, 15.5, 0.5 ) 42 ~0.859 43 > y = {{alias}}( 5.0, 7.4, 0.4 ) 44 ~0.131 45 46 > y = {{alias}}( 2.0, 0.0, 0.5 ) 47 NaN 48 > y = {{alias}}( 2.0, -2.0, 0.5 ) 49 NaN 50 51 > y = {{alias}}( NaN, 20.0, 0.5 ) 52 NaN 53 > y = {{alias}}( 0.0, NaN, 0.5 ) 54 NaN 55 > y = {{alias}}( 0.0, 20.0, NaN ) 56 NaN 57 58 > y = {{alias}}( 2.0, 20, -1.0 ) 59 NaN 60 > y = {{alias}}( 2.0, 20, 1.5 ) 61 NaN 62 63 64 {{alias}}.factory( r, p ) 65 Returns a function for evaluating the cumulative distribution function (CDF) 66 of a negative binomial distribution with number of successes until 67 experiment is stopped `r` and success probability `p`. 68 69 Parameters 70 ---------- 71 r: number 72 Number of successes until experiment is stopped. 73 74 p: number 75 Success probability. 76 77 Returns 78 ------- 79 cdf: Function 80 Cumulative distribution function (CDF). 81 82 Examples 83 -------- 84 > var myCDF = {{alias}}.factory( 10, 0.5 ); 85 > var y = myCDF( 3.0 ) 86 ~0.046 87 > y = myCDF( 11.0 ) 88 ~0.668 89 90 See Also 91 -------- 92