Neutrosophic Exponential {ntsDists} | R Documentation |
Density, distribution function, quantile function and random
generation for the neutrosophic exponential distribution with the
parameter rate
= \theta_N
.
dnsExp(x, rate)
pnsExp(q, rate, lower.tail = TRUE)
qnsExp(p, rate)
rnsExp(n, rate)
x |
a vector or matrix of observations for which the pdf needs to be computed. |
rate |
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 |
a vector or matrix of probabilities for which the quantile needs to be computed. |
n |
number of random values to be generated. |
The neutrosophic exponential distribution with parameter \theta_N
has density
f_N(x)=\theta_N \exp \left(-x \theta_N\right)
for x \ge 0
and \theta_N \in (\theta_L, \theta_U)
,
the rate parameter must be a positive interval and x \ge 0
.
dnsExp
gives the density function
pnsExp
gives the distribution function
qnsExp
gives the quantile function
rnsExp
generates random values from the neutrosophic exponential distribution.
Duan, W., Q., Khan, Z., Gulistan, M., Khurshid, A. (2021). Neutrosophic Exponential Distribution: Modeling and Applications for Complex Data Analysis, Complexity, 2021, 1-8.
# Example 4 of Duan et al. (2021)
data <- matrix(c(4, 4, 3.5, 3.5, 3.9, 4.1, 4.2, 4.2, 4.3, 4.6, 4.7, 4.7),
nrow = 6, ncol = 2, byrow = TRUE)
dnsExp(data, rate = c(0.23, 0.24))
dnsExp(x = c(4, 4.1), rate = c(0.23, 0.24))
dnsExp(4, rate = c(0.23, 0.23))
# The cumulative distribution function for the nuetrosophic observation (4,4.1)
pnsExp(c(4, 4.1), rate = c(0.23, 0.24), lower.tail = TRUE)
pnsExp(4, rate = c(0.23, 0.24))
# The first percentile
qnsExp(p = 0.1, rate = 0.25)
# The quantiles
qnsExp(p = c(0.25, 0.5, 0.75), rate = c(0.24, 0.25))
# Simulate 10 numbers
rnsExp(n = 10, rate = c(0.23, 0.24))