KISS launches the new KISS webinar series. The information about our first KISS webinar is provided below. I am looking forward to seeing you there!
Date and Time: 4-5pm ET, March 12 (Fri)
Zoom address: https://psu.zoom.us/j/96312135796
Speaker: Jae-Kwang Kim
Title: Statistical Inference after Kernel Ridge Regression Imputation under Item Nonresponse
Abstract: Kernel Ridge Regression (KRR) is a modern regression technique based on the theory of Reproducing Kernel Hilbert Space. We use KRR to develop imputation for handling item nonresponse. While the KRR is potentially promising for imputation, its statistical properties are not fully investigated in the literature. We first establish the root-n consistency of the KRR imputation estimators and show that it is optimal in the sense that it achieves the lower bound of the semiparametric asymptotic variance. A consistent variance estimator is also proposed by a novel application of the KRR estimator of the density ratio function. Results from a limited simulation study are also presented to confirm our theory.