Neutrosophic Rayleigh {ntsDists}

Neutrosophic Rayleigh Distribution

Description

Density, distribution function, quantile function and random generation for the neutrosophic Rayleigh distribution with parameter \theta_N.

Usage

dnsRayleigh(x, theta)

pnsRayleigh(q, theta, lower.tail = TRUE)

qnsRayleigh(p, theta)

rnsRayleigh(n, theta)

Arguments

x

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

theta

the shape parameter, which must be a positive interval.

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 Rayleigh distribution with parameter \theta_N has the density

f_N(x)=\frac{x}{\theta_N^2} \exp\{-\frac{1}{2}\left(\frac{x}{\theta_N}\right)^2\}

for \theta_N \in (\theta_L, \theta_U), which must be a positive interval and x \ge 0.

Value

dnsRayleigh gives the density function

pnsRayleigh gives the distribution function

qnsRayleigh gives the quantile function

rnsRayleigh generates random variables from the Neutrosophic Rayleigh Distribution.

References

Khan, Z., Gulistan, M., Kausar, N. and Park, C. (2021). Neutrosophic Rayleigh Model With Some Basic Characteristics and Engineering Applications, in IEEE Access, 9, 71277-71283.

Examples

data(remission)
dnsRayleigh(x = remission, theta = c(9.6432, 9.8702))

pnsRayleigh(q = 20, theta = c(9.6432, 9.8702))

# Calculate quantiles
qnsRayleigh(p = c(0.25, 0.5, 0.75), theta = c(9.6432, 9.8702))

# Simulate 10 values
rnsRayleigh(n = 10, theta = c(9.6432, 9.8702))