R Language Random Numbers Generator Generating random numbers using various density functions
Example
Below are examples of generating 5 random numbers using various probability distributions.
Uniform distribution between 0 and 10
runif(5, min=0, max=10)
[1] 2.1724399 8.9209930 6.1969249 9.3303321 2.4054102
Normal distribution with 0 mean and standard deviation of 1
rnorm(5, mean=0, sd=1)
[1] -0.97414402 -0.85722281 -0.08555494 -0.37444299 1.20032409
Binomial distribution with 10 trials and success probability of 0.5
rbinom(5, size=10, prob=0.5)
[1] 4 3 5 2 3
Geometric distribution with 0.2 success probability
rgeom(5, prob=0.2)
[1] 14 8 11 1 3
Hypergeometric distribution with 3 white balls, 10 black balls and 5 draws
rhyper(5, m=3, n=10, k=5)
[1] 2 0 1 1 1
Negative Binomial distribution with 10 trials and success probability of 0.8
rnbinom(5, size=10, prob=0.8)
[1] 3 1 3 4 2
Poisson distribution with mean and variance (lambda) of 2
rpois(5, lambda=2)
[1] 2 1 2 3 4
Exponential distribution with the rate of 1.5
rexp(5, rate=1.5)
[1] 1.8993303 0.4799358 0.5578280 1.5630711 0.6228000
Logistic distribution with 0 location and scale of 1
rlogis(5, location=0, scale=1)
[1] 0.9498992 -1.0287433 -0.4192311 0.7028510 -1.2095458
Chi-squared distribution with 15 degrees of freedom
rchisq(5, df=15)
[1] 14.89209 19.36947 10.27745 19.48376 23.32898
Beta distribution with shape parameters a=1 and b=0.5
rbeta(5, shape1=1, shape2=0.5)
[1] 0.1670306 0.5321586 0.9869520 0.9548993 0.9999737
Gamma distribution with shape parameter of 3 and scale=0.5
rgamma(5, shape=3, scale=0.5)
[1] 2.2445984 0.7934152 3.2366673 2.2897537 0.8573059
Cauchy distribution with 0 location and scale of 1
rcauchy(5, location=0, scale=1)
[1] -0.01285116 -0.38918446 8.71016696 10.60293284 -0.68017185
Log-normal distribution with 0 mean and standard deviation of 1 (on log scale)
rlnorm(5, meanlog=0, sdlog=1)
[1] 0.8725009 2.9433779 0.3329107 2.5976206 2.8171894
Weibull distribution with shape parameter of 0.5 and scale of 1
rweibull(5, shape=0.5, scale=1)
[1] 0.337599112 1.307774557 7.233985075 5.840429942 0.005751181
Wilcoxon distribution with 10 observations in the first sample and 20 in second.
rwilcox(5, 10, 20)
[1] 111 88 93 100 124
Multinomial distribution with 5 object and 3 boxes using the specified probabilities
rmultinom(5, size=5, prob=c(0.1,0.1,0.8))
[,1] [,2] [,3] [,4] [,5]
[1,] 0 0 1 1 0
[2,] 2 0 1 1 0
[3,] 3 5 3 3 5
