Bootstrap prediction intervals in beta regressions

We address the issue of constructing prediction intervals for responses that assume values in the standard unit interval, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$(0,1)$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mo stretchy="false">(</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </math> </EquationSource> </InlineEquation>. The response is modeled using the class of beta regression models and we introduce percentile and <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$\hbox {BC}_a$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msub> <mtext>BC</mtext> <mi>a</mi> </msub> </math> </EquationSource> </InlineEquation> (bias-corrected and accelerated) bootstrap prediction intervals. We present Monte Carlo evidence on the finite sample behavior of such intervals. An empirical application is presented and discussed. Copyright Springer-Verlag Berlin Heidelberg 2014