“…QR has led to interesting studies in the FLRMs. For the QR settings in scalar-on-function regression models, where the response is scalar and predictors consist of random curves (see, e.g., Cardot et al, 2005;Ferraty et al, 2005;Cardot et al, 2007;Chen and M üller, 2012;Kato, 2012;Tang and Cheng, 2014;Yu et al, 2016;Yao et al, 2017;Ma et al, 2019;Sang and Cao, 2020;Chaouch et al, 2020). On the other hand, for the QR settings in the context of function-on-scalar regression models, where the response variable involves random curves and predictors are scalar variables (see, e.g., Kim, 2007;Wang et al, 2009;Yang et al, 2020;Liu et al, 2020).…”