The purpose of the paper is to provide a general method based on conditional quantile curves to predict record values from preceding records. The predictions are based on conditional median (or median regression) curves. Moreover, conditional quantiles curves are used to provide confidence bands for these predictions. The method is based on the recently introduced concept of multivariate distorted distributions that are used instead of copulas to represent the dependence structure. This concept allows us to compute the conditional quantile curves in a simple way. The theoretical findings are illustrated with a non-parametric model (standard uniform), two parametric models (exponential and Pareto), and a non-parametric procedure for the general case. A real data set and a simulated case study in reliability are analysed.

本文的目的是提供一种基于条件分位数曲线的通用方法，以从先前的记录中预测记录值。预测基于条件中值（或中值回归）曲线。此外，条件分位数曲线用于为这些预测提供置信区间。该方法基于最近引入的多元失真分布概念，该概念用于代替 copula 来表示依赖结构。这个概念允许我们以简单的方式计算条件分位数曲线。理论结果用一个非参数模型（标准均匀模型）、两个参数模型（指数和帕累托）和一个用于一般情况的非参数程序来说明。分析了一个真实的数据集和一个模拟的可靠性案例研究。