Neutrosophic Geometric {ntsDists}

Neutrosophic Geometric Distribution

Description

Density, distribution function, quantile function and random generation for the neutrosophic Geometric distribution with parameter prob = p_N.

Usage

dnsGeom(x, prob)

pnsGeom(q, prob, lower.tail = TRUE)

qnsGeom(p, prob)

rnsGeom(n, prob)

Arguments

x

a vector or matrix of observations for which the pdf needs to be computed.

prob

probability of success on each trial, prob\in (0,1).

q

a vector or matrix of quantiles for which the cdf needs to be computed.

lower.tail

logical; if TRUE (default), probabilities are P(X \leq x); otherwise, P(X >x).

p

a vector or matrix of probabilities for which the quantile needs to be computed.

n

number of random values to be generated.

Details

The neutrosophic Geometric distribution with parameter p_N has the density

f_X(x)=p_N\left(1-p_N\right)^x

for p_N \in (p_L, p_U) which must be 0<p_N<1 and x \in \{0, 1, 2, \ldots\}.

Value

dnsGeom gives the probability mass function

pnsGeom gives the distribution function

qnsGeom gives the quantile function

rnsGeom generates random variables from the Geometric Distribution.

References

Granados, C. (2022). Some discrete neutrosophic distributions with neutrosophic parameters based on neutrosophic random variables. Hacettepe Journal of Mathematics and Statistics, 51(5), 1442-1457.

Examples

# One person participates each week with a ticket in a lottery game, where
# the probability of winning the first prize is (10^(-8), 10^(-6)).
# Probability of one persons wins at the fifth year?

dnsGeom(x = 5, prob = c(1e-8, 1e-6))

# Probability of one persons wins after 10 years?
pnsGeom(q = 10, prob = c(1e-8, 1e-6))
pnsGeom(q = 10, prob = c(1e-8, 1e-6), lower.tail = FALSE)
# Calculate the quantiles
qnsGeom(p = c(0.25, 0.5, 0.75), prob = c(1e-8, 1e-6))
# Simulate 10 numbers
rnsGeom(n = 10, prob = c(1e-8, 1e-6))