The function ZIBB
defines the zero inflated beta binomial distribution, a three parameter distribution,
for a gamlss.family
object to be used in GAMLSS fitting using the function gamlss()
.
The functions dZIBB
, pZIBB
, qZIBB
and rZINN
define the
density, distribution function, quantile function
and random generation for the zero inflated beta binomial, ZIBB
, distribution.
The function ZABB
defines the zero adjusted beta binomial distribution, a three parameter distribution, for a
gamlss.family
object to be used in GAMLSS fitting using the function gamlss()
. The functions dZABB
, pZABB
,
qZABB
and rZABB
define the
density, distribution function, quantile function
and random generation for the zero inflated beta binomial, ZABB()
, distribution.
ZABB(mu.link = "logit", sigma.link = "log", nu.link = "logit")
ZIBB(mu.link = "logit", sigma.link = "log", nu.link = "logit")dZIBB(x, mu = 0.5, sigma = 0.5, nu = 0.1, bd = 1, log = FALSE)
dZABB(x, mu = 0.5, sigma = 0.1, nu = 0.1, bd = 1, log = FALSE)
pZIBB(q, mu = 0.5, sigma = 0.5, nu = 0.1, bd = 1, lower.tail = TRUE, log.p = FALSE)
pZABB(q, mu = 0.5, sigma = 0.1, nu = 0.1, bd = 1, lower.tail = TRUE, log.p = FALSE)
qZIBB(p, mu = 0.5, sigma = 0.5, nu = 0.1, bd = 1, lower.tail = TRUE, log.p = FALSE)
qZABB(p, mu = 0.5, sigma = 0.1, nu = 0.1, bd = 1, lower.tail = TRUE, log.p = FALSE)
rZIBB(n, mu = 0.5, sigma = 0.5, nu = 0.1, bd = 1)
rZABB(n, mu = 0.5, sigma = 0.1, nu = 0.1, bd = 1)
The functions ZIBB
and ZABB
return a gamlss.family
object which can be used to fit a
zero inflated or zero adjusted beta binomial distribution respectively in the gamlss()
function.
Defines the mu.link
, with "logit" link as the default for the mu
parameter.
Other links are "probit" and "cloglog"'(complementary log-log)
Defines the sigma.link
, with "log" link as the default for the sigma
parameter.
Defines the sigma.link
, with "logit" link as the default for the mu
parameter.
Other links are "probit" and "cloglog"'(complementary log-log)
vector of (non-negative integer) quantiles
vector of positive probabilities
vector of positive dispertion parameter
vector of positive probabilities
vector of binomial denominators
vector of probabilities
vector of quantiles
number of random values to return
logical; if TRUE, probabilities p are given as log(p)
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]
Mikis Stasinopoulos, Bob Rigby
The definition of the zero adjusted beta binomial distribution, ZABB
and the the zero inflated beta binomial distribution, ZIBB
, are given in p. 527 and p. 528 of of Rigby et al. (2019), respectively.
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.
Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, tools:::Rd_expr_doi("10.18637/jss.v023.i07")..
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC. tools:::Rd_expr_doi("10.1201/b21973")
(see also https://www.gamlss.com/).
gamlss.family
, NBI
, NBII
ZIBB()
ZABB()
# creating data and plotting them
dat <- rZIBB(1000, mu=.5, sigma=.5, nu=0.1, bd=10)
r <- barplot(table(dat), col='lightblue')
dat1 <- rZABB(1000, mu=.5, sigma=.2, nu=0.1, bd=10)
r1 <- barplot(table(dat1), col='lightblue')
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