randomvariate

func Binomial ¶

func Binomial(n int, p float64) int

Binomial draws n samples from a binomial probability distribution given by the probability p. Another way to imagine this is that the function counts the number of sucessful draws. If n = 1, the function draws once and the result can either be 1 or 0. The probability of successfully drawing is given by the slice p.

func Multinomial ¶

func Multinomial(n int, p []float64) []int

Multinomial draws n samples from a probability distribution given by the set of probabilities p. Uses the inversion method which may be inefficient when the number of categories and number of samples are both large.

func MultinomialA ¶

func MultinomialA(n int, p []float64) []int

MultinomialA draws n samples from a probability distribution given by the set of probabilities p. Uses the alias method. Faster when dealing with a larger number of categories and number of samples.

func MultinomialLog ¶

func MultinomialLog(n int, logP []float64) []int

MultinomialLog draws n samples from a log-probability distribution given by the set of probabilities p. Note that the log probabilities are in the format log(p) where p is from 0 to 1. If p = 0, the log-probability should be encoded as negative infinity.

func MultinomialLog1p ¶

func MultinomialLog1p(n int, logP []float64) []int

MultinomialLog1p draws n samples from a log-probability distribution given by the set of probabilities p. Note that the log probabilities are actually log(1+p) where p is from 0 to 1. This prevents solves the problem of computing log probability of 0.

func Poisson ¶

func Poisson(lambda float64) int

func PoissonXL ¶

func PoissonXL(lambda float64) int

func Round ¶

func Round(x float64, e int) float64

Round rounds a value from zero based on the given units place. For example, the value to be round is 0.05 and the given unit is 0.1, Round will return 0.1 as it rounds 0.05 to the nearest tenths place.