gap {NovelDistns} | R Documentation |
Computes the pdf, cdf, quantile, and random numbers and estimates the parameters of the exponentiated gull alpha power family of distribution specified by the cdf.
F(x,{\Theta}) = \left[\frac{\alpha G(x)}{\alpha^{G(x)}}\right]
where \theta
is the baseline family parameter vector.Here, the baseline G
refers to the cdf of: exponential, rayleigh and weibull.
rgap(n, dist, param)
qgap(p, dist, param, log.p = FALSE, lower.tail = TRUE)
pgap(data, dist, param, log.p = FALSE, lower.tail = TRUE)
dgap(data, dist, param, log = FALSE)
mlgap(data, dist,starts, method="SANN")
n |
number of realizations to be generated. |
p |
quantile value between 0 and 1. |
data |
Vector of observations. |
param |
parameter vector |
log |
If |
log.p |
If |
lower.tail |
If |
dist |
The name of family's pdf including: " |
method |
the method for optimizing the log likelihood function. It can be one of |
starts |
initial values of |
A vector of the same length as data
, giving the pdf values computed at data
.
A vector of the same length as data
, giving the cdf values computed at data
.
A vector of the same length as p
, giving the quantile values computed at p
.
A vector of the same length as n
, giving the random numbers realizations.
A sequence of goodness-of-fit statistics such as: Akaike Information Criterion (AIC
), Consistent Akaike Information Criterion (CAIC
), Bayesian Information Criterion (BIC
), Hannan-Quinn information criterion (HQIC
), Cramer-von Misses statistic (CM
), Anderson Darling statistic (AD
), log-likelihood statistic (log
). The Kolmogorov-Smirnov (KS
) test statistic and corresponding p-value
and the convergence status.
Mutua Kilai, Gichuhi A. Waititu, Wanjoya A. Kibira
Muhammad et al (2020) A Gull Alpha Power Weibull distribution with applications to real and simulated data. https://doi.org/10.1371/journal.pone.0233080
x=runif(10,min=0,max=1)
rgap(10,"exp",c(0.3,0.5))
qgap(0.6,"exp",c(0.3,0.5))
pgap(x,"exp",c(0.3,0.5))
dgap(x,"exp",c(0.3,0.5))
mlgap(x,"exp",c(0.3,0.5))