Neutrosophic Kumaraswamy {ntsDists}

Neutrosophic Kumaraswamy Distribution

Description

Density, distribution function, quantile function and random generation for the neutrosophic Kumaraswamy distribution with shape parameters \alpha_N and \beta_N.

Usage

dnsKumaraswamy(x, shape1, shape2)

pnsKumaraswamy(q, shape1, shape2, lower.tail = TRUE)

qnsKumaraswamy(p, shape1, shape2)

rnsKumaraswamy(n, shape1, shape2)

Arguments

x

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

shape1

the shape parameter, which must be a positive interval.

shape2

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 genelambdad.

Details

The neutrosophic Kumaraswamy distribution with parameters \alpha_N and \beta_N has density

f_N(x) = \alpha_N \beta_N x^{\alpha_N-1}(1-x^{\alpha_N})^{\beta_N - 1}

for 0 \le x \le 1, \alpha_N \in (\alpha_L, \alpha_U) and \beta_N \in (\beta_L, \beta_U) are shape parameters.

Value

pnsKumaraswamy gives the distribution function

dnsKumaraswamy gives the density

qnsKumaraswamy gives the quantile function

rnsKumaraswamy generates random values from the neutrosophic Kumaraswamy distribution.

References

Ahsan-ul-Haq, M. (2022). Neutrosophic Kumaraswamy Distribution with Engineering Application, Neutrosophic Sets and Systems, 49, 269-276.

Examples

dnsKumaraswamy(x = c(0.5, 0.1), shape1 = c(0.23, 0.24), shape2 = c(1, 2))
dnsKumaraswamy(0.5, shape1 = c(0.23, 0.24), shape2 = c(1, 2))


# The cumulative distribution function for the nuetrosophic observation (4,4.1)
pnsKumaraswamy(q = c(.8, .1), shape1 = c(0.23, 0.24), shape2 = c(1, 2))
# The first percentile
qnsKumaraswamy(p = 0.1, shape1 = 0.24, shape2 = 2)

# The quantiles
qnsKumaraswamy(p = c(0.25, 0.5, 0.75), shape1 = c(0.23, 0.24), shape2 = c(1, 2))

# Simulate 10 numbers
rnsKumaraswamy(n = 10, shape1 = c(0.23, 0.24), shape2 = c(1, 2))