论文检索

凹回归中的一致性AI 解读

For each $t$ in some subinterval $T$ of the real line let $F_t$ be a distribution function with mean $m(t)$. Suppose $m(t)$ is concave. Let $t_1, t_2, \cdots$ be a sequence of points in $T$ and let $Y_1, Y_2, \cdots$ be an independent sequence of random variables such that the distribution function of $Y_k$ is $F_{t_k}$. We consider estimators $m_n(t) = m_n(t; Y_1, \cdots, Y_n)$ which are concave in $t$ and which minimize $\sum^n_{i=1} \lbrack m_n(t_i; Y_1, \cdots, Y_n) - Y_i\rbrack^2$…

三角阵观测点下积分回归估计的一致性AI 解读

Let $\mu$ be a continuous mean regression function defined on $U$, the unit cube in $N$-dimensional Euclidean space. Let $F$ be a distribution function with support in $U$, and let $M$ denote the indefinite integral of $\mu$ with respect to $F$. This paper provides consistency results, including rates of convergence, for a certain estimator of $M$ in the case that the $n$th estimate is based on observations at points $\mathbf{t}_{n1},\cdots, \mathbf{t}_{nn}$ of $U$. The…

Wilcoxon 检验对某类样本间依赖的稳健性AI 解读

Robustness properties of the two-sample Wilcoxon test are established when the assumption of independence between samples is weakened to allow pairing. In particular, the test is shown to be (asymptotically) conservative when the bivariate distribution governing the pairing is positively quadrant dependent.

单调回归的一致性研究AI 解读

For each $t$ in some subset $T$ of $N$-dimensional Euclidean space let $F_t$ be a distribution function with mean $m(t)$. Suppose $m(t)$ is non-decreasing in each of the coordinates of $t$. Let $t_1, t_2,\cdots$ be a sequence of points in $T$ and let $Y_1, Y_2,\cdots$ be an independent sequence of random variables such that the distribution function of $Y_k$ is $F_{t_k}$. Estimators $\hat{m}_n(t; Y_1,\cdots, Y_n)$ of $m(t)$ which are monotone in each coordinate of $t$ and…