Photo by tamiminaser from unsplash
Abstract Using a wavelet basis, Chesneau and Shirazi study the estimation of one-dimensional regression functions in a biased non parametric model over L2 risk (see Chesneau, C and Shirazi, E.… Click to show full abstract
Abstract Using a wavelet basis, Chesneau and Shirazi study the estimation of one-dimensional regression functions in a biased non parametric model over L2 risk (see Chesneau, C and Shirazi, E. Non parametric wavelet regression based on biased data, Communication in Statistics – Theory and Methods, 43: 2642–2658, 2014). This article considers d-dimensional regression function estimation over Lp (1 ⩽ p < ∞) risk. It turns out that our results reduce to the corresponding theorems of Chesneau and Shirazi’s theorems, when d = 1 and p = 2.
Journal Title: Communications in Statistics - Theory and Methods
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!