Description Usage Arguments Details Examples

The pZOIP function defines the cumulative distribution function of the ZOIP distribution.

1 2 |

`q` |
quantiles vector. |

`mu` |
vector of location parameters. |

`sigma` |
vector of scale parameters. |

`p0` |
parameter of proportion of zeros. |

`p1` |
Parameter of proportion of ones. |

`family` |
choice of the parameterization or distribution, family = 'R-S' parameterization beta distribution Rigby and Stasinopoulos, 'F-C' distribution Beta parametrization Ferrari and Cribari-Neto, 'Original' Beta distribution classic parameterization, 'Simplex' simplex distribution. |

`lower.tail` |
logical; if TRUE (default), probabilities will be P [X <= x], otherwise, P [X> x]. |

`log.p` |
logical; if TRUE, the probabilities of p will be given as log (p). |

x has ZOIP distribution with shape parameters "*μ*", scale "*σ*", proportion of zeros "*p0*" and proportion of ones "* p1* ",
has density: *p0* if *x = 0*, *p1* if *x = 1*, *(1-p0-p1) f (x; μ, σ)* yes *0 <x <1*.

where *p0 ≥ 0* represents the probability that *x = 0, p1 ≥ 0* represents the probability
that *x = 1, 0 ≤ p0 + p1 ≤ 1* and *f (x; μ, σ)* represents some of the functions of
probability density for proportional data, such as the beta distribution with its different parameterizations
and the simplex distribution.

When family =' R-S 'uses the beta distribution with beta parameterization Rigby and Stasinopoulos (2005) which has a beta distribution function.
*μ* is the parameter of mean and shape, plus *σ* is the dispersion parameter of the distribution.
family =' F-C 'distribution Beta parametrization Ferrari and Cribari-Neto (2004), where *σ = φ*, *φ* is a precision parameter.
family =' Original 'beta distribution original parametrization where *μ = a*, a parameter of form 1; *σ = b*, b parameter of form 2.
family =' Simplex 'simplex distribution. proposed by Barndorff-Nielsen and Jørgensen (1991)

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library(ZOIP)
pZOIP(q=0.5, mu = 0.2, sigma = 0.5, p0 = 0.2, p1 = 0.2,family='R-S',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0.2, p1 = 0.2,family='F-C',log = FALSE)
pZOIP(q=0.5, mu = 0.6, sigma = 2.4, p0 = 0.2, p1 = 0.2,family='Original',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0.2, p1 = 0.2,family='Simplex',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 0.5, p0 = 0, p1 = 0.2,family='R-S',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0, p1 = 0.2,family='F-C',log = FALSE)
pZOIP(q=0.5, mu = 0.6, sigma = 2.4, p0 = 0, p1 = 0.2,family='Original',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0, p1 = 0.2,family='Simplex',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 0.5, p0 = 0.2, p1 = 0,family='R-S',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0.2, p1 = 0,family='F-C',log = FALSE)
pZOIP(q=0.5, mu = 0.6, sigma = 2.4, p0 = 0.2, p1 = 0,family='Original',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0.2, p1 = 0,family='Simplex',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 0.5, p0 = 0, p1 = 0,family='R-S',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0, p1 = 0,family='F-C',log = FALSE)
pZOIP(q=0.5, mu = 0.6, sigma = 2.4, p0 = 0, p1 = 0,family='Original',log = FALSE)
pZOIP(q=0.5, mu = 0.2, sigma = 3, p0 = 0, p1 = 0,family='Simplex',log = FALSE)
``` |

jucdiaz/ZOIP documentation built on Aug. 17, 2018, 2:24 a.m.

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