Neutrosophic Poisson {ntsDists} | R Documentation |
Density, distribution function, quantile function and random
generation for the neutrosophic Poisson distribution with
parameter \lambda_N
.
dnsPois(x, lambda)
pnsPois(q, lambda, lower.tail = TRUE)
qnsPois(p, lambda)
rnsPois(n, lambda)
x |
a vector or matrix of observations for which the pdf needs to be computed. |
lambda |
the mean, 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 Poisson distribution with parameter \lambda_N
has the density
f_N(x)= \exp\{-\lambda_N\} \frac{\left(\lambda_N\right)^x}{x !}
for \lambda_N \in (\lambda_L, \lambda_U)
which must be a positive
interval and x \in \{0, 1, 2, \ldots\}
.
dnsPois
gives the probability mass function
pnsPois
gives the distribution function
qnsPois
gives the quantile function
rnsPois
generates random variables from the neutrosophic Poisson Distribution.
Alhabib, R., Ranna, M. M., Farah, H., Salama, A. A. (2018). Some neutrosophic probability distributions. Neutrosophic Sets and Systems, 22, 30-38.
# In a company, Phone employee receives phone calls, the calls arrive with
# rate of [1 , 3] calls per minute, we will calculate
# the probability that the employee will not receive any call within a minute
dnsPois(x = 0, lambda = c(1, 3))
# the probability that employee would not receive any call within 5 minutes
dnsPois(x = 0, lambda = c(5, 15))
# the probability that the employee will receive at least one call within a minute
pnsPois(q = 1, lambda = c(1, 3), lower.tail = FALSE)
# the probability that the employee will receive at most three calls within 5 minutes
pnsPois(q = 3, lambda = c(5, 15), lower.tail = TRUE)
# Calcaute the quantiles
qnsPois(p = c(0.25, 0.5, 0.75), lambda = c(1, 3))
# Simulate 10 values
rnsPois(n = 10, lambda = 1)