# fixed1: Fixed-effects beta regression with inflation at 1 In zoib: Bayesian Inference for Beta Regression and Zero-or-One Inflated Beta Regression

## Description

Internal function called by function zoib; Fits a fixed-effects beta regression a response variable bounded within (0, 1].

## Usage

 ```1 2``` ```fixed1(y, n, xmu.1, p.xmu, xsum.1, p.xsum, x1.1, p.x1, prior1, prec.int, prec.DN, lambda.L1, lambda.L2, lambda.ARD, link, n.chain,inits, seed) ```

## Arguments

 `y` A univariate response variable taking value from (0, 1]. `n` Number of rows in the data set. `xmu.1` Design matrix associated with the fixed effects in the linear predictor of g(mean of the beta piece), where g() is link function. `p.xmu` Number of columns in xmu.1. `xsum.1` Design matrix associated with the fixed effects in linear predictor of the log(dispersion parameter of the beta piece). `p.xsum` Number of columns in xsum.1. `x1.1` Design matrix associated with the fixed effects in linear predictor of the g(Pr(y=1)), where g() is link function. `p.x1` Number of columns in x1.1. `prior1` Internally generated data (a vector of dimension 4). Prior choice for the regression coefficients in each of the 4 linear predictors of the 4 link functions. `prec.int` The precision parameter in the prior distributions (diffuse normal) of the intercepts in the linear predictors. `prec.DN` The precision parmeter in the prior distributions of the regression coefficients in the linear predictors if the diffuse normal prior is chosen. `lambda.ARD` The scale parameter in the prior distributions of the regression coefficients in the linear predictors if the ARD prior is chosen. `lambda.L1` The scale parameter in the prior distributions of the regression coefficients in the linear predictors if the L1-like prior is chosen. `lambda.L2` The scale parameter in the prior distributions of the regression coefficients in the linear predictors if the L2-like prior is chosen. `link` Internally generated variable containing the information on the choice of link functions for the mean of the beta piece. `n.chain` Number of chains for the MCMC sampling. `inits` initial parameter for model parameters. `seed` seeds for results reproducibility

## Value

Internal function. Returned values are used internally

## Author(s)

Fang Liu (fang.liu.131@nd.edu)

See Also as `zoib`