Description Usage Arguments Examples
Cumulative probability function of empirical distribution using linear interpolation
Quantile function of Empirical Distribution
Random generation function of Empirical Distribution
Density function of Empirical Distribution based on simulation
1 2 3 4 5 6 7 | pempirical(q, cdf)
qempirical(p, cdf)
rempirical(n, cdf)
dempirical(x, cdf)
|
q |
Value of the variable |
cdf |
empirical distribution (cdf for continuous distribution and pmf for discrete distribution) |
p |
Value of the probability |
n |
Number of samples |
x |
Value of the variable |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | #discrete distribution
pempirical(c(3,5,10),matrix(c(0.1,0.2,0.3,0.05,0.05,0.2,0.1,1:6,10),7,2))
#continuous distribution
pempirical(350,matrix(c(seq(0.01,1,0.01),cumprod(c(1,rep(1.1,99)))),100,2))
#discrete distribution
qempirical(c(0.3,0.65,1),matrix(c(0.1,0.2,0.3,0.05,0.05,0.2,0.1,1:6,10),7,2))
#continuous distribution
qempirical(c(0.3,0.65,0.8),matrix(c(seq(0.01,1,0.01),cumprod(c(1,rep(1.1,99)))),100,2))
#discrete distribution
rempirical(100,matrix(c(0.1,0.2,0.3,0.05,0.05,0.2,0.1,1:6,10),7,2))
#continuous distribution
rempirical(100,matrix(c(seq(0.01,1,0.01),cumprod(c(1,rep(1.1,99)))),100,2))
#discrete distribution
dempirical(3,matrix(c(0.1,0.2,0.3,0.05,0.05,0.2,0.1,1:6,10),7,2))
#continuous distribution
dempirical(30,matrix(c(seq(0.01,1,0.01),qnorm(seq(0.01,1,0.01),30,20)),100,2))
|
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