Neutrosophic Weibull {ntsDists} | R Documentation |
Density, distribution function, quantile function and random
generation for the neutrosophic Weibull distribution with scale
parameter \alpha_N
and shape
parameter \beta_N
.
dnsWeibull(x, shape, scale)
pnsWeibull(q, shape, scale, lower.tail = TRUE)
qnsWeibull(p, shape, scale)
rnsWeibull(n, shape, scale)
x |
a vector or matrix of observations for which the pdf needs to be computed. |
shape |
shape parameter, which must be a positive interval. |
scale |
scale 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 Rayleigh distribution with parameters
\alpha_N
and \beta_N
has the density
f_N(x)=\frac{\beta_N}{\alpha_N^{\beta_N}} x^{\beta_N-1}
\exp\{-\left(x / \alpha_N\right)^{\beta_N}\}
for \beta_N \in (\beta_L, \beta_U)
the shape parameter must
be a positive interval, \alpha_N \in (\alpha_L,\alpha_U)
,
the scale parameter which be a positive interval, and x > 0
.
dnsWeibull
gives the density function
pnsWeibull
gives the distribution function
qnsWeibull
gives the quantile function
rnsWeibull
generates random variables from the neutrosophic Weibull dDistribution.
Alhasan, K. F. H. and Smarandache, F. (2019). Neutrosophic Weibull distribution and Neutrosophic Family Weibull Distribution, Neutrosophic Sets and Systems, 28, 191-199.
data(remission)
dnsWeibull(x = remission, shape = c(1.0519, 1.0553), scale = c(9.3370, 9.4544))
pnsWeibull(q = 20, shape = c(1.0519, 1.0553), scale = c(9.3370, 9.4544))
# Calculate quantiles
qnsWeibull(p = c(0.25, 0.5, 0.75), shape = c(1.0519, 1.0553), scale = c(9.3370, 9.4544))
# Simulate 10 numbers
rnsWeibull(n = 10, shape = c(1.0519, 1.0553), scale = c(9.3370, 9.4544))