#Cran.r project.org the beta distribution how to
Information about the package and how to install it can be found at.
#Cran.r project.org the beta distribution code
Additionally, the package provides Stan ( Stan Development Team 2018) code for performing Bayesian analysis with the unifed including a function for fitting Bayesian unifed GLMs. It also contains a family that can be used within the glm function of R. It is called unifed and contains functions for the density, distribution, quantiles and random generator. This makes it suitable to be used as the response variable of a Generalized Linear Model (GLM).Īn R (see ( R Core Team 2017) and ( Quijano Xacur 2019b)) package has been developed to work with this distribution. It can be characterized as the only exponential dispersion family containing the uniform distribution. It is a continuous distribution with support on the interval (0,1). # mod1<-gamlss(dat1~1,family=BE) # fits a constant for mu and sigma Gamlss.family, BE, LOGITNO, GB1, BEINF ExamplesīE()# gives information about the default links for the beta distribution M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017)įlexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. (2006) Instructions on how to use the GAMLSS package in R.Īccompanying documentation in the current GAMLSS help files, (see also ). (2019)ĭistributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC, doi: 10.1201/9780429298547.
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Generalized additive models for location, scale and shape,(with discussion), Note that for BE, mu is the mean and sigma a scale parameter contributing to the variance of y Author(s)īob Rigby and Mikis Stasinopoulos References The expected value of y is mu and the variance is sigma^2*mu*(1-mu).īE() and BEo() return a gamlss.family object which can be used to fit a beta distribution in the gamlss() function. The reparametrization in the function BE() is In the gamlss implementation of BEo α=μ and β>σ. Logical if TRUE (default), probabilities are P Logical if TRUE, probabilities p are given as log(p). The sigma link function with default logit QBEo(p, mu = 0.5, sigma = 0.2, lower.tail = TRUE, log.p = FALSE) PBEo(q, mu = 0.5, sigma = 0.2, lower.tail = TRUE, log.p = FALSE) PBE(q, mu = 0.5, sigma = 0.2, lower.tail = TRUE, log.p = FALSE) Generation for the BE and BEo parameterizations respectively of the beta distribution.īE(mu.link = "logit", sigma.link = "logit")ĭBE(x, mu = 0.5, sigma = 0.2, log = FALSE)
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The functions dBE and dBEo, pBE and pBEo, qBE and qBEo and finally rBE and rBEĭefine the density, distribution function, quantile function and random BEo() is the original parameterizations of the beta distribution as in dbeta() with BE() has mean equal to the parameter muĪnd sigma as scale parameter, see below. Gamlss.family object to be used in GAMLSS fitting The functions BE() and BEo() define the beta distribution, a two parameter distribution, for a
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The beta distribution for fitting a GAMLSS Description