We propose two test statistics for use in inverse regression problems "Y"="K""&thgr;"+"ϵ", where "K" is a given linear operator which cannot be continuously inverted. Thus, only noisy, indirect observations "Y" for the function "&thgr;" are available. Both test statistics have a counterpart in classical...

This paper presents a quadratic one-step bootstrap method for binary response data. Rather than resampling from the original sample, the proposed method resamples summands appearing in the quadratic approximation of the estimates. It enjoys the same computational simplicity as its linear...

Estimating all parameters in a multiparameter response model as smooth functions of an explanatory variable is very similar to estimating the different components of an additive model for the response mean. It is shown that, in a general estimating framework, local polynomial backfitting...

Nonparametric tests for the null hypothesis that a function has a prescribed form are developed and applied to data sets with missing observations. Omnibus nonparametric tests such as the order selection tests, do not need to specify a particular alternative parametric form, and have power...

In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline estimators. We consider three types of estimation methods: (i) as a standard (fixed effect) nonparametric model, (ii) using the mixed model framework with the spline coefficients as random effects...

To test if a density "f" is equal to a specified "f"₀, one knows by the Neyman-Pearson lemma the form of the optimal test at a specified alternative "f"₁. Any non-parametric density estimation scheme allows an estimate of "f". This leads to estimated likelihood ratios. Properties are studied of...

We study the class of penalized spline estimators, which enjoy similarities to both regression splines, without penalty and with fewer knots than data points, and smoothing splines, with knots equal to the data points and a penalty controlling the roughness of the fit. Depending on the number of...