非线性自回归序列L1估计的渐近分布

由于时间序列数据中经常出现的厚尾特征使得通常的估计方法不再具有渐近的正态分布,在误差项二阶矩有限的条件下考虑了非线性自回归序列的L_1估计.采用局部线性近似的方法得到了具有凸样本路径的随机过程,在此基础上利用凸样本路径随机过程弱收敛的性质证明了非线性自回归序列L_1估计的渐近正态性及无偏性.     

重尾非线性自回归模型自加权M-估计的渐近分布

考虑非线性自回归模型x_t=f(x_t-1,…,x_t-p,θ)+∈_t,其中θ为q维未知参数,{∈_t}为随机误差.在允许误差方差无穷的重尾条件下,构造θ的自加权M-估计,并证明了该估计的渐近正态性.最后通过数值模拟,在随机误差服从某些重尾分布的条件下,说明自加权M-估计比最小二乘和L₁估计更有效.     

Ψ-混合异方差误差下半参数回归模型的加权小波估计

考虑半参数回归模型yi=xiβ+g(ti)+σiei, i=1,2,…,n,其中(zi,ti,ui)是固定设计点列,ei为Ψ-混合随机误差.用小波估计方法得到了参数,非参数及误差方差的加权小波估计量.在相当一般的条件下,得到了这些小波估计量的渐近正态性及弱收敛速度.     

部分线性自回归模型中误差方差的核估计

基于非参数函数的核估计,构造了部分线性自回归模型中误差四阶矩的相合估计,从而给出了误差方差核估计的渐近正态性,并通过模拟算例和实例说明了其应用.     

具有外生变量部分线性自回归模型的样条估计

考虑自回归模型Y_t=θ~TX_t g(Zt) ε_t,t=1,…,n,其中X_t=(Y_(t-1),…,Y_(t-d))~T,Z_t为实值外生随机变量,θ=(θ_1,…,θ_d)~T为待估参数向量,g为未知非参数光滑函数．基于多项式样条方法,在一定的条件下,给出了θ的估计的渐近正态性,得到了g的估计的收敛速度．模拟例子验证了所得的理论结果．     

具有外生变量部分线性自回归模型的样条估计

考虑自回归模型Yt=θTXt+g(Zt)+Et,t=1,…,n,其中Xt=(Y-1,…,Yt-d)T,Zt为实值外生随机变量,θ=(θ1,…,θd)T为待估参数向量,g为未知非参数光滑函数.基于多项式样条方法,在一定的条件下,给出了θ的估计的渐近正态性,得到了g的估计的收敛速度.模拟例子验证了所得的理论结果.     

门限自回归模型参数最小二乘估计的强收敛速度

本文在给定门限自回归模型阶数、门限和延迟参数的情况下，证明了一般门限自回归模型参数和残差方差的最小二乘估计的强收敛速度为Ｏ（（ｌｏｇｌ９ｏｇｎ／ｎ）１／２），并证明了残差方差的最小二乘估计具有渐近正态性．     

ACD模型自加权LAD估计的渐近性质

针对高频数据建模中常用的自回归条件持续期(ACD)模型,在允许误差方差无穷的条件下,构造模型参数的自加权最小一乘(SLAD)估计,并证明了该估计的相合性和渐近正态性.数值模拟显示SLAD估计比拟极大似然估计和最小一乘估计更稳健,最后将其应用于青岛海尔和宝信软件这两只股票的价格持续期建模.     

左截断数据下非线性模型的加权分位数回归

左截断数据是一类具有特殊结构的缺失数据,当且仅当研究变量大于一定的阈值时才能取得观察值.本文针对左截断数据下的非线性回归模型,提出了加权分位数估计方法,利用加权方式处理左截断缺失数据,取得了与完整数据相近的估计结果.并在一定假设条件下,证明了所提估计方法的一致性和渐近正态性等大样本性质,最后通过数值模拟展现所提估计方法的有限样本表现.     

异方差回归模型近邻型估计的相合性

本文研究异方差回归模型Ｙｉ＾（ｎ）＝ｇ（ｘｉ＾（ｎ））＋εｉ＾（ｎ）,ｉ＝１,…,ｎ,其中ｇ是右实函数,ｘｉ＾（ｎ）是非随机设计点列,εｉ＾（ｎ）是随机误差,文中定义了一类ｇ（ｘ）的近邻型估计ｇｎ（ｘ）＝（ｎ）∑（ｉ＝１）Ｗｍ（ｘ）Ｙｉ＾（ｎ）,得到了ｒ阶平均相全和渐近正态性,特别,在（∞）∑（ｎ＝１）（ｎ）∑（ｉ＝１）Ｅ／εｉ＾（ｎ）／＾ｓ／（ｎｉ）＾ｓ／ｒ〈∞,ｍａｘＥ（１≤ｉ≤ｎ）／εｉ（＾     

A test for independence of two stationary infinite order autoregressive processes

This paper considers the independence test for two stationary infinite order autoregressive processes. For a test, we follow the empirical process method and construct the Cramér-von Mises type test statistics based on the least squares residuals. It is shown that the proposed test statistics behave asymptotically the same as those based on true errors. Simulation results are provided for illustration.     

Existence results for a nonlinear version of Rotenberg model with infinite maturation velocities

In this paper, we present some existence results on L¹ spaces of a nonlinear boundary value problem derived from a model introduced by Rotenberg (1983) describing the growth of a cell population. Each cell of this population is distinguished by its degree of maturity μ ∈ [0,1] and its maturation velocity v. The biological boundary at μ = 0 and μ = 1 are fixed and tightly coupled through the mitosis. At mitosis, daughter cells and mother cells are related by a general reproduction rule, which covers all known biological ones. In this work, the maturation velocity is allowed to be infinite, that is, v ∈ [0, + ∞ ). This hypothesis introduce some mathematical difficulties, which are overcomed by using a measure of weak noncompactness adapted to the problem and a recent fixed point theorem (Theorem 3.2) involving weakly compact operators on nonreflexive Banach spaces. Copyright © 2014 John Wiley & Sons, Ltd.     

非线性l1问题的光滑近似算法

为非线性l1问题的求解构造了光滑逼近函数.首先将非线性l1问题转化为等价的不可微优化问题;其次通过两步提出光滑逼近函数的一般性构造方法;最后进行了数值仿真.文中介绍了光滑逼近函数的有关性质,指出相关文献已有的光滑函数方法是本文的特例,并证明了方法的收敛性及有效性.     

A note on self-normalized Dickey-Fuller test for unit root in autoregressive time series with GARCH errors

In this article, the unit root test for AR（p） model with GARCH errors is considered. The Dickey-Fuller test statistics are rewritten in the form of self-normalized sums, and the asymptotic distribution of the test statistics is derived under the weak conditions.     

非线性l1问题的调节熵函数法

提出求解非线性l1问题的调节熵函数法．介绍了非线性l1问题的调节熵函数的有关性质、调节熵函数算法及其收敛性,最后给出数值实例．     

On the cusum of squares test for variance change in nonstationary and nonparametric time series models

In this paper we consider the problem of testing for a variance change in nonstationary and nonparametric time series models. The models under consideration are the unstable AR(q) model and the fixed design nonparametric regression model with a strong mixing error process. In order to perform a test, we employ the cusum of squares test introduced by Inclán and Tiao (1994,J. Amer. Statist. Assoc.,89, 913–923). It is shown that the limiting distribution of the test statistic is the sup of a standard Brownian bridge as seen in iid random samples. Simulation results are provided for illustration.     

PDα‐type distributed learning control for nonlinear fractional‐order multiagent systems

This paper considers the consensus tacking problem for nonlinear fractional‐order multiagent systems by presenting a PD^α‐type iterative learning control update law with initial learning mechanisms. The asymptotical convergence of the proposed distributed learning algorithm is strictly proved by using the properties of fractional calculus. A sufficient condition is derived to guarantee the whole multiagent system achieving an asymptotic output consensus. An illustrative example is given to verify the theoretical results.     

Conditioned limit theorem for virtual waiting time process of the GI/G/1 queue

We prove that in the queueing system GI/G/1 with traffic intensity one, the virtual waiting time process suitably scaled, normed and conditioned by the event that the length of the first busy period exceeds n converges to the Brownian meander process, as n .