time-to-botec

Benchmark sampling in different programming languages
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repl.txt (2082B)


      1 
      2 {{alias}}( x, r, p )
      3     Evaluates the natural logarithm of the probability mass function (PMF) for a
      4     negative binomial distribution with number of successes until experiment is
      5     stopped `r` and 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 logPMF.
     30 
     31     Examples
     32     --------
     33     > var y = {{alias}}( 5.0, 20.0, 0.8 )
     34     ~-1.853
     35     > y = {{alias}}( 21.0, 20.0, 0.5 )
     36     ~-2.818
     37     > y = {{alias}}( 5.0, 10.0, 0.4 )
     38     ~-4.115
     39     > y = {{alias}}( 0.0, 10.0, 0.9 )
     40     ~-1.054
     41     > y = {{alias}}( 21.0, 15.5, 0.5 )
     42     ~-3.292
     43     > y = {{alias}}( 5.0, 7.4, 0.4 )
     44     ~-2.976
     45 
     46     > y = {{alias}}( 2.0, 0.0, 0.5 )
     47     NaN
     48     > y = {{alias}}( 2.0, -2.0, 0.5 )
     49     NaN
     50     > y = {{alias}}( 2.0, 20, -1.0 )
     51     NaN
     52     > y = {{alias}}( 2.0, 20, 1.5 )
     53     NaN
     54 
     55     > y = {{alias}}( NaN, 20.0, 0.5 )
     56     NaN
     57     > y = {{alias}}( 0.0, NaN, 0.5 )
     58     NaN
     59     > y = {{alias}}( 0.0, 20.0, NaN )
     60     NaN
     61 
     62 
     63 {{alias}}.factory( r, p )
     64     Returns a function for evaluating the natural logarithm of the probability
     65     mass function (PMF) of a negative binomial distribution with number of
     66     successes until experiment is stopped `r` and success probability `p`.
     67 
     68     Parameters
     69     ----------
     70     r: number
     71         Number of successes until experiment is stopped.
     72 
     73     p: number
     74         Success probability.
     75 
     76     Returns
     77     -------
     78     logpmf: Function
     79         Logarithm of probability mass function (PMF).
     80 
     81     Examples
     82     --------
     83     > var mylogPMF = {{alias}}.factory( 10, 0.5 );
     84     > var y = mylogPMF( 3.0 )
     85     ~-3.617
     86     > y = mylogPMF( 5.0 )
     87     ~-2.795
     88 
     89     See Also
     90     --------
     91