A simple method is introduced for finding large sample, boundary-respecting confidence intervals (CIs) for the two-sample Mann–Whitney measure, θ=Pr{X>Y}−Pr{X<Y}. This natural separation measure for two distributions occurs in stress–strength models, receiver operating characteristic curves, and nonparametrics generally. The usual estimate of θ is a centred version of the well-known Mann–Whitney statistic. Previous Wald-type CIs are not boundary-respecting. The difficulty is typically nonparametric, whereby appealing exact distributions hold only for one null parameter value, preventing the formulation of true distribution-free inference for non-null values. Here, the rank method setting and a result, that stochastic ordering is equivalent ...
Given a sample X/,. .. ,x" from a distribution F, the problem of constructing nonparametric confiden...
Consider a semiparametric transformation model of the form Λθ(Y ) = m(X)+ε, where Y is a univariate ...
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) [5] and...
A simple method is introduced for finding large sample, boundary-respecting confidence intervals (CI...
We develop a simple but useful generalization of the classical Wilcoxon-MannWhitney statistic. A nor...
A two-sample test is studied which rejects the null hypothesis of equal population medians when two ...
One-Sample ProblemsIntroduction Location Model Geometry and Inference in the Location Model Examples...
The paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach whic...
<p>Suppose one has a collection of parameters indexed by a (possibly infinite dimensional) set. Give...
none2noLet X and Y be two independent continuous random variables. We discuss three techniques to ob...
The two-sample problem occurs in many scientific fields, with a major frequency in environmental and...
This article deals with the confidence interval estimation of [theta]1, when the parameters [theta]1...
The problem of testing for a monotone trend in proportions has been frequently disccussed in the lit...
This paper considers semiparametric efficient estimation of conditional moment models with possibly ...
Sample size determination methods are considered for hypothesis testing about location parameters of...
Given a sample X/,. .. ,x" from a distribution F, the problem of constructing nonparametric confiden...
Consider a semiparametric transformation model of the form Λθ(Y ) = m(X)+ε, where Y is a univariate ...
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) [5] and...
A simple method is introduced for finding large sample, boundary-respecting confidence intervals (CI...
We develop a simple but useful generalization of the classical Wilcoxon-MannWhitney statistic. A nor...
A two-sample test is studied which rejects the null hypothesis of equal population medians when two ...
One-Sample ProblemsIntroduction Location Model Geometry and Inference in the Location Model Examples...
The paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach whic...
<p>Suppose one has a collection of parameters indexed by a (possibly infinite dimensional) set. Give...
none2noLet X and Y be two independent continuous random variables. We discuss three techniques to ob...
The two-sample problem occurs in many scientific fields, with a major frequency in environmental and...
This article deals with the confidence interval estimation of [theta]1, when the parameters [theta]1...
The problem of testing for a monotone trend in proportions has been frequently disccussed in the lit...
This paper considers semiparametric efficient estimation of conditional moment models with possibly ...
Sample size determination methods are considered for hypothesis testing about location parameters of...
Given a sample X/,. .. ,x" from a distribution F, the problem of constructing nonparametric confiden...
Consider a semiparametric transformation model of the form Λθ(Y ) = m(X)+ε, where Y is a univariate ...
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) [5] and...