neutrostat (version 0.0.2)

ngam: Neutrosophic Gamma Distribution with Characteristics

Description

Computes various properties of the Neutrosophic Gamma distribution, including its density, cumulative distribution function (CDF), quantiles,random numbers with summary statistics,PDF and CDF plots of the distribution.

Usage

dngam(x, scale_l, scale_u, shape_l, shape_u)
pngam(q, scale_l, scale_u, shape_l, shape_u)
qngam(p, scale_l, scale_u, shape_l, shape_u)
rngam(n, scale_l, scale_u, shape_l, shape_u, stats = FALSE)
plot_npdfgam(scale_l, scale_u, shape_l, shape_u, x = c(0, 5),
                         color.fill = "lightblue", color.line = "blue",
                         title = "PDF Neutrosophic Gamma Distribution",
                         x.label = "x", y.label = "Density")
plot_ncdfgam(scale_l, scale_u, shape_l, shape_u, x = c(0, 5),
                         color.fill = "lightblue", color.line = "blue",
                         title = "CDF Neutrosophic Gamma Distribution",
                         x.label = "x", y.label = "Cumulative Probability")

Value

dngam returns the PDF values

pngam returns the lower tail CDF values.

qngam returns the quantile values

rngam return random values with summary statistics of the simulated data

plot_npdfgam returns PDF plot at given values of distributional parameters

plot_ncdfgam returns CDF plot at given values of distributional parameters

Arguments

x

A numeric vector of observations for which the function will compute the corresponding distribution values.

n

number of random generated values

scale_l

A positive numeric value representing the lower bound of the scale parameter of the Neutrosophic Gamma distribution.

scale_u

A positive numeric value representing the upper bound of the scale parameter of the Neutrosophic Gamma distribution. This must be greater than or equal to rate_l.

shape_l

A positive numeric value representing the lower bound of the shape parameter of the Neutrosophic Gamma distribution.

shape_u

A positive numeric value representing the upper bound of the shape parameter of the Neutrosophic Gamma distribution.

p

A vector of probabilities for which the function will compute the corresponding quantile values

q

A vector of quantiles for which the function will compute the corresponding CDF values

stats

Logical; if TRUE, the function returns summary statistics of the generated random data (e.g., mean, standard deviation, quantiles, skewness, and kurtosis).

color.fill

A string representing the color for neutrosophic region.

color.line

A string representing the color used for the line of the PDF or CDF in the plots.

title

A string representing the title of the plot.

x.label

A string representing the label for the x-axis.

y.label

A string representing the label for the y-axis.

Author

Zahid Khan

Details

The function computes various properties of the Neutrosophic Gamma distribution. Depending on the function variant used (e.g., density, CDF, quantiles), it will return the corresponding statistical measure for each input value of x in case of random number generation from Neutrosophic Gamma distribution. Moreover basic plots of PDF and CDF can be visualized.

References

Khan Z, Al-Bossly A, Almazah M, Alduais FS. (2021). On Statistical Development of Neutrosophic Gamma Distribution with Applications to Complex Data Analysis, Complexity, 2021, 1-8.doi:10.1155/2021/3701236

Examples

# random number Generation with summary statistics

rngam(10, scale_l = 2, scale_u = 4, shape_l = 1, shape_u = 1, stats = TRUE)

# PDF values
x <- 2
scale_l <- 1
scale_u <- 2.0
shape_l<-0.5
shape_u<-2
dngam(x, scale_l, scale_u, shape_l, shape_u)

# CDF values
q <- 1.5
scale_l <- 1
scale_u <- 2.0
shape_l<-0.5
shape_u<-2.0
pngam(q, scale_l, scale_u, shape_l, shape_u)

# Quantile values

p <- 0.5
scale_l <- 1
scale_u <- 2.0
shape_l<-0.5
shape_u<-2
qngam(p, scale_l, scale_u, shape_l, shape_u)

# PDF PLOT
scale_l <- 1
scale_u <- 1
shape_l<-2
shape_u<-3
plot_npdfgam(scale_l, scale_u, shape_l, shape_u, x = c(0, 5))

# CDF PLOT
scale_l <- 1
scale_u <- 1
shape_l<-2
shape_u<-3
plot_ncdfgam(scale_l, scale_u, shape_l, shape_u, x = c(0, 5))