repl.txt (1715B)
1 2 {{alias}}( x, n, p ) 3 Evaluates the probability mass function (PMF) for a binomial distribution 4 with number of trials `n` and success probability `p` at a value `x`. 5 6 If provided `NaN` as any argument, the function returns `NaN`. 7 8 If provided a number of trials `n` which is not a nonnegative integer, the 9 function returns `NaN`. 10 11 If `p < 0` or `p > 1`, the function returns `NaN`. 12 13 Parameters 14 ---------- 15 x: number 16 Input value. 17 18 n: integer 19 Number of trials. 20 21 p: number 22 Success probability. 23 24 Returns 25 ------- 26 out: number 27 Evaluated PMF. 28 29 Examples 30 -------- 31 > var y = {{alias}}( 3.0, 20, 0.2 ) 32 ~0.205 33 > y = {{alias}}( 21.0, 20, 0.2 ) 34 0.0 35 > y = {{alias}}( 5.0, 10, 0.4 ) 36 ~0.201 37 > y = {{alias}}( 0.0, 10, 0.4 ) 38 ~0.006 39 > y = {{alias}}( NaN, 20, 0.5 ) 40 NaN 41 > y = {{alias}}( 0.0, NaN, 0.5 ) 42 NaN 43 > y = {{alias}}( 0.0, 20, NaN ) 44 NaN 45 > y = {{alias}}( 2.0, 1.5, 0.5 ) 46 NaN 47 > y = {{alias}}( 2.0, -2.0, 0.5 ) 48 NaN 49 > y = {{alias}}( 2.0, 20, -1.0 ) 50 NaN 51 > y = {{alias}}( 2.0, 20, 1.5 ) 52 NaN 53 54 55 {{alias}}.factory( n, p ) 56 Returns a function for evaluating the probability mass function (PMF) of a 57 binomial distribution with number of trials `n` and success probability `p`. 58 59 Parameters 60 ---------- 61 n: integer 62 Number of trials. 63 64 p: number 65 Success probability. 66 67 Returns 68 ------- 69 pmf: Function 70 Probability mass function (PMF). 71 72 Examples 73 -------- 74 > var mypmf = {{alias}}.factory( 10, 0.5 ); 75 > var y = mypmf( 3.0 ) 76 ~0.117 77 > y = mypmf( 5.0 ) 78 ~0.246 79 80 See Also 81 -------- 82