从$A^{p}_{\alpha}$到$A^{\infty}(\varphi)$的加权复合算子

设$u \in H(D), \ \phi$为$D$上的解析自映射,定义$H(D)$上的加权复合算子为$u C_{\phi}(f)=$$uf\circ\phi$, \ $f\in H(D)$.本文得到了从$A^{p}_{\alpha}$到$A^{\infty}(\varphi)\ (A_{0}^{\infty}(\varphi))$的加权复合算子$u C_{\phi}$的有界性和紧性的充要条件.     

有结构变化的半参数回归模型

结合半参数回归模型和含未知变点的结构变化模型提出 一个新的模型\,---\,有结构变化的半参数回归模型, 给出了新模型的有关参数$\beta,\beta^\ast,\gamma,k$的加权最小二乘估计和$f(t)$的核估计, 证明了参数\, $\beta,\beta^\ast,\gamma$的估计的$\sqrt{n}$\,-相合性, 强相合性, 讨论了模型的检验等问题, 并进一步通过随机模拟验证了新模型的优越性.     

一类复映射$z\leftarrow e^{i\phi}(\bar{z})^\alpha+c~ (\alpha<0)$的广义M集

本文分析了一类复映射$z \leftarrow e^{i\phi }(\bar {z})^\alpha +c\{\alpha < 0,\phi \in [0,2\pi)\}$的临界点的性质,给出了广义Mandelbrot集 (简称广义M集)的定义,并构造出一系列广义M集.利用复变函数理论和计算机制图相结合的实验数学的方法,本文对广义M集的结构和演化进行了研究,结果表明: 1). 广义M集的几何结构依赖于参数$\alpha$, $R$和$\phi$; 2). 整数阶广义M集具有对称性和分形特征; 3). 小     

亚BCI-代数的$(\alpha,\beta)$-软理想

首先将软集的参数集赋予亚BCI-代数, 给出了亚BCI-代数的$(\alpha,\beta)$-软理想的概念.当$U=[0,1], \alpha=U, \beta=\phi$时,相应地就得到了亚BCI-代数的犹豫模糊理想的概念.研究了亚BCI-代数的$(\alpha,\beta)$-软理想的一些重要性质.最后讨论了亚BCI-代数的$(\alpha,\beta)$-软理想的同态像和原像的性质.     

完备的$\nu$-广义度量空间上的不动点定理[英文]

本文对度量空间中$C$类函数的压缩映射进行推广. 在完备的$\nu$-广义度量空间上, 利用构造迭代序列的方法, 证明了关于($\psi$,$\phi$)-类型压缩映射的不动点定理. 并且证明了广义的$F$类型压缩和广义$\theta$类型压缩映射.     

球面上$\ell_1$正则优化的随机临近梯度方法

本文研究球面上的$\ell_1$正则优化问题,其目标函数由一般光滑函数项和非光滑$\ell_1$正则项构成,且假设光滑函数的随机梯度可由随机一阶oracle估计.这类优化问题被广泛应用在机器学习,图像、信号处理和统计等领域.根据流形临近梯度法和随机梯度估计技术,提出一种球面随机临近梯度算法.基于非光滑函数的全局隐函数定理,分析了子问题解关于参数的Lipschtiz连续性,进而证明了算法的全局收敛性.在基于随机数据集和实际数据集的球面$\ell_1$正则二次规划问题、有限和SPCA问题和球面$\ell_1$正则逻辑回归问题上数值实验结果显示所提出的算法与流形临近梯度法、黎曼随机临近梯度法相比CPU时间上具有一定的优越性.     

因子上非线性混合三重积保持映射

设$\mathcal{A}$, $\mathcal{B}$是两个因子且$\dim\mathcal{A}>4$.本文证明了双射$\phi:\mathcal{A}\rightarrow\mathcal{B}$ 满足对所有的$A,B,C\in\mathcal A$有$\phi([A,B]\bullet C)=[\phi(A),\phi(B)]\bullet\phi(C)$当且仅当$\phi$是线性*-同构, 共轭线性*- 同构,负的线性*-同构, 负的共轭线性*-同构.     

可平面图的r-hued染色[英文]

令$k>0,r>0$是两个整数.图$G$的一个$r$-hued 染色是一个正常$k$-染色$\phi$使得每个度为$d(v)$的顶点$v$相邻至少$\textrm{min}\{d(v), r\}$个不同的颜色.图$G$的$r$-hued色数是使得$G$存在$r$-hued 染色的最小整数$k$,记为$\chi_r(G)$.文章证明了,若$G$为不含$i$-圈,$4\leq i\leq 9$,的可平面图, 则$ \chi_r(G)\leq r+5$.这一结果意味着对于无4-9圈的可平面图, $r$-hued 染色猜想成立.     

纵向数据下半参数回归模型估计的渐近性质

本文考虑纵向数据下半参数回归模型: $y_{ij}=x_{ij}'\beta+g(t_{ij})+e_ij},\;i=1,\cdots,m,\;j=1,\cdots,n_i$. 基于最小二乘法和一般的非参数权函数方法给出了模型中参数$\beta$和回归函数$g(\cdot)$的估计, 并在适当条件下证明了$\beta$估计量的渐近正态性和$g(\cdot)$估计量的最优收敛速度\bd 模拟结果表明我们的估计方法在有限样本情形有良好的效果     

尺度参数变点的非参数检验

本文讨论了尺度参数模型参数变点的假设检验问题\bd 基于两样本$U$\,-统计量, 我们给出了两个检验, 并且研究了检验统计量分布的极限性质\bd 我们证明了这两个检验统计量的极限分布分别是$\sup\limits_{0相似文献   

Parameter change test for location‐scale time series models with heteroscedasticity based on bootstrap

This study considers the bootstrap cumulative sum (CUSUM) test for a parameter change in location‐scale time series models with heteroscedasticity. The CUSUM test has been popular for detecting an abrupt change in time series models because it performs well in many applications. However, it has severe size distortions in many situations. As a remedy, we consider the bootstrap CUSUM test, particularly focusing on the CUSUM test based on score vectors, and demonstrate the weak consistency of the bootstrap test for its justification. A simulation study and data analysis are conducted for illustration.     

至多一个变点的$\Gamma$分布的统计推断及在金融中的应用

对至多一个变点的Γ分布,即X1,X2…,Xn为一列相互独立的随机变量序列,且X1,X2,…,X[nΥ0]i．i．d～Γ(x;ν1,λ1),X[nΥ0] 1,X[nΥ0] 2,…,Xn i．i．d～Γ(x;ν2,λ2),其中Υ0未知,称Υ0为该序列的变点．在利用第一型极值分布逼近文中提出统计量的分布的基础上,给出了变点Υ0估计(?)的相合性及强弱收敛速度．最后给出了在金融序列上的应用．     

System availability behavior of some stationary dependent sequences

We consider the system availability behavior of a one-unit repairable system when the failure and the repair times are generated by a stationary dependent sequence of random variables. We obtain the general expression for the point availability, and discuss the nature of the availability measure for two time series models: a first-order exponential moving average process and a first-order exponential autoregressive process.     

On the estimation of optimal batch sizes in the analysis of simulation output

The estimation of the variance of point estimators is a classical problem of stochastic simulation. A more specific problem addresses the estimation of the variance of a sample mean from a steady-state autocorrelated process. Many proposed estimators of the variance of the sample mean are parameterized by batch size. A critical problem is to find an appropriate batch size that provides a good tradeoff between bias and variance. This paper proposes a procedure for determining the optimal batch size to minimize the mean squared error of estimators of the variance of the sample mean. This paper also presents the results of empirical studies of the procedure. The experiments involve symmetric two-state Markov chain models, first-order autoregressive processes, seasonal autoregressive processes, and queue-waiting times for several M/M/1 queueing models. The empirical results indicate that the estimation procedure works nearly as well as it would if the parameters of the processes were known.     

粘性系数依赖于密度的Korteweg型不可压流体的强解问题

研究一类Korteweg型不可压流体模型的强解问题.针对粘性系数依赖于密度的情形,当初始值满足兼容性条件(9)对,证明了强解的局部存在性和唯一性.我们在这指出,本文允许初始真空存在.     

Monitoring parameter change in AR(p) time series models

Sequential tests that are generalizations of Page’s CUSUM tests are proposed for detecting an abrupt change in any parameter, or in any collection of parameters of an autoregressive time series model. These tests accommodate nuisance parameters. They are based on large sample approximations to the efficient score vector under the null hypothesis of no change and under the alternative. The empirical power of the tests is evaluated in a simulation study. The new method performs better than the existing ones found in the literature if the criterion is the type I error probability, which can be unacceptably high for methods that minimize the expected value of the reaction time.     

Modeling Zero Inflation in Count Data Time Series with Bounded Support

Real count data time series often show an excessive number of zeros, which can form quite different patterns. We develop four extensions of the binomial autoregressive model for autocorrelated counts with a bounded support, which can accommodate a broad variety of zero patterns. The stochastic properties of these models are derived, and ways of parameter estimation and model identification are discussed. The usefulness of the models is illustrated, among others, by an application to the monetary policy decisions of the National Bank of Poland.     

Tail dependence of random variables from ARCH and heavy-tailed bilinear models

Discussed in this paper is the dependent structure in the tails of distributions of random variables from some heavy-tailed stationary nonlinear time series. One class of models discussed is the first-order autoregressive conditional heteroscedastic (ARCH) process introduced by Engle (1982). The other class is the simple first-order bilinear models driven by heavy-tailed innovations. We give some explicit formulas for the asymptotic values of conditional probabilities used for measuring the tail dependence between two random variables from these models. Our results have significant meanings in finance.     

$\alpha$阶星象亚纯函数

令$S(p)$表示单位圆盘$\mathbb{D}$上在$p\in(0,1)$处有一个简单极点的单叶亚纯函数全体.令$\alpha\in[0,1)$,我们用$\Sigma^{*}(p,\omega_{0},\alpha)$表示$f\in S(p)$使得$\hat{\mathbb{C}}\setminus f(\mathbb{D})$是关于不动点$\omega_{0}\neq0$, $\infty$星象的$\alphga$阶区域的函数全体.在本文中,$f\in\Sigma^{*}(p,\omega_{0},\alpha)$的一些解析刻画条件和系数估计被考虑.     

基于残差加权经验过程方法的自回归模型分布变点监测

Change monitoring of distribution in time series models is an important issue.This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series,which is based on a weighed empirical process of residuals with weights equal to the regressors.The asymptotic properties of our monitoring statistic are derived under the null hypothesis of no change in distribution.The finite sample properties are investigated by a simulation.As it turns out,the procedure is not only able to detect distributional changes but also changes in the regression coefficient and mean.Finally,we apply the statistic to a groups of financial data.