Héctor ArayaNatalia BahamondeTania RoaTorres, SoledadSoledadTorresFermín, LisandroLisandroFermín2025-04-122025-04-122021-05-0510.5705/ss.202020.04572-s2.0-85161630086https://cris-uv-2.scimago.es/handle/123456789/1814WOS:001021573400001In this study, we prove the strong consistency of the least squares estimator in a random sampled linear regression model with long-memory noise and an independent set of random times given by renewal process sampling. Additionally, we illustrate how to work with a random number of observations up to time T = 1. A simulation study is provided to illustrate the behavior of the different terms, as well as the performance of the estimator under various values of the Hurst parameter H.enacceso restringidoStatistics And ProbabilityStatistics, Probability And Uncertaintyarticle