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 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...

Warping is an approach to the reduction and analysis of phase variability in functional observations, by applying a smooth bijection to the function argument. We propose a natural representation of warping functions in terms of a new type of elementary functions named 'warping component...

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...

This papers offers a theoretical explanation for the stylized fact that forecast combinations with estimated optimal weights often perform poorly in applications. The properties of the forecast combination are typically derived under the assumption that the weights are fixed, while in practice...