In this article, we study the problem of variable screening in multiple nonparametric regression model. The proposed methodology is based on the fact that the partial derivative of the regression function with respect to the irrelevant variable should be negligible. The Statistical property of the proposed methodology is investigated under both cases : (i) when the variance of the error term is known, and (ii) when the variance of the error term is unknown. Moreover, we establish the practicality of our proposed methodology for various simulated and real data related to interdisciplinary sciences such as Economics, Finance and other sciences.

翻译：在本条中,我们研究了多重非参数回归模型中的可变筛选问题,拟议方法基于一个事实,即与无关变量有关的回归功能的部分衍生物应可忽略不计,对拟议方法的统计属性在两种情况下都进行了调查:(一) 当已知错误术语的差异,和(二) 当误差术语的差异不详时,我们确定了与经济学、金融学和其他科学等跨学科科学有关的各种模拟和真实数据的拟议方法的实用性。