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Outcomes of continuous proportions arise in many applied areas. Such data are typically measured as percentages, rates or proportions confined in the unitary interval. In this paper, the R package simplexreg which provides dispersion model fitting of the simplex distribution is introduced to model such proportional outcomes. The maximum likelihood method and generalized estimating equations techniques are available for parameter estimation in cross-sectional and longitudinal studies, respectively. This paper presents methods and algorithms implemented in the package, including parameter estimation, model checking as well as density, cumulative distribution, quantile and random number generating functions of the simplex distribution. The package is applied to real data sets for illustration.