Abstract We investigate a simple objective for nonlinear instrumental variable (IV) regression based on kernelized conditional moment restriction known as maximum (MMR). The MMR is formulated by maximizing the interaction between residual and instruments belonging to unit ball in reproducing kernel Hilbert space. First, it allows us simplify IV an empirical risk minimization problem, where func...

In the last few decades, several works have been undertaken in context of proportional reversed hazard rates (PRHR) but any specific statistical methodology for PRHR hypothesis is absent literature. This paper proposes a two-sample nonparametric test based on two independent samples to verify assumption. Based consistent U-statistic three methodologies developed exploiting U-statistics theory, ...

* We are grateful to Sophie Hesling for her assistance with data collection. Abstract We show that the full asymptotic distribution for Watson's 2 N U statistic, modified for discrete data, can be computed by standard methods. Previous approximate percentiles for the uniform multinomial case are found to be accurate. More extensive percentiles are presented for this distribution, and for the di...

We investigate the large-sample behavior of change-point tests based on weighted two-sample U-statistics, in case short-range dependent data. Under some mild mixing conditions, we establish convergence test statistic to an extreme value distribution. A simulation study shows that are superior non-weighted versions when occurs near boundary time interval, while they loose power center.

Consider a nonseparable model Y = R(X,U) where Y and X are observed, while U is unobserved and conditionally independent of X. This paper provides the first nonparametric test of whether R takes the form of a transformation model, meaning that Y is monotonic in the sum of a function of X plus a function of U . Transformation models of this form are commonly assumed in economics, including, e.g....

Many clustering techniques aim at optimizing empirical criteria that are of the form of a U -statistic of degree two. Given a measure of dissimilarity between pairs of observations, the goal is to minimize the within cluster point scatter over a class of partitions of the feature space. It is the purpose of this paper to define a general statistical framework, relying on the theory of U -proces...

We address the problem of testing in every brain voxel v whether at least u out of n conditions (or subjects) considered shows a real effect. The only statistic suggested so far, the maximum p-value method, fails under dependency (unless u=n) and in particular under positive dependency that arises if all stimuli are compared to the same control stimulus. Moreover, it tends to have low power und...