Sequential Estimation of the Parameters in a Trigonometric Regression Model with the Gaussian Coloured Noise

This paper considers the estimation problem for a trigonometric regression model with the noise specified by the Ornstein–Uhlenbeck process with unknown parameter. We propose a sequential procedure which ensures a prescribed mean square precision uniformly in the nuisance parameter. The asymptotic behaviour of the procedure duration mean has been studied. This revised version was published online in August 2006 with corrections to the Cover Date.     

轴线起爆式螺线管型爆磁压缩发生器理论模型

 对轴线起爆式螺线管型爆磁压缩发生器进行了理论模型研究，建立了爆炸管的一维爆轰驱动模型、螺线管内空间磁场强度分布模型、爆炸管外表面磁压力模型和发生器系统的等效电路模型等，对此类发生器的物理过程进行系统描述。在此基础上，编制了相应的零维数值模拟程序CEMG 1.0，利用该程序分别对四种不同模型参数的发生器进行了理论计算和参数优化，并对其中一模型发生器爆炸管外表面的磁压力及其引起的剩余电感进行了计算，给出了剩余电感与初始输入条件及负载电感的关系，从而得到该模型的输出性能极限。对理论模型的正确性进行了实例验算证明。     

Regression quantiles for unstable autoregressive models

This paper investigates regression quantiles (RQ) for unstable autoregressive models. The uniform Bahadur representation of the RQ process is obtained. The joint asymptotic distribution of the RQ process is derived in a unified manner for all types of characteristic roots on or outside the unit circle. It involves stochastic integrals in terms of a sequence of independent and identically distributed multivariate Brownian motions with correlated components. The related L-estimator is also discussed. The asymptotic distributions of the RQ and the L-estimator corresponding to the nonstationary componentwise arguments can be transformed into a function of a normal random variable and a sequence of i.i.d. univariate Brownian motions. This is different from the analysis based on the LSE in the literature. As an auxiliary theorem, a weak convergence of a randomly weighted residual empirical process to the stochastic integral of a Kiefer process is established. The results obtained in this paper provide an asymptotic theory for nonstationary time series processes, which can be used to construct robust unit root tests.     

Nonparametric estimation of distributions with categorical and continuous data

In this paper we consider the problem of estimating an unknown joint distribution which is defined over mixed discrete and continuous variables. A nonparametric kernel approach is proposed with smoothing parameters obtained from the cross-validated minimization of the estimator's integrated squared error. We derive the rate of convergence of the cross-validated smoothing parameters to their ‘benchmark’ optimal values, and we also establish the asymptotic normality of the resulting nonparametric kernel density estimator. Monte Carlo simulations illustrate that the proposed estimator performs substantially better than the conventional nonparametric frequency estimator in a range of settings. The simulations also demonstrate that the proposed approach does not suffer from known limitations of the likelihood cross-validation method which breaks down with commonly used kernels when the continuous variables are drawn from fat-tailed distributions. An empirical application demonstrates that the proposed method can yield superior predictions relative to commonly used parametric models.     

Relative intensity noise of mode-locked fiber grating external cavity semiconductor lasers

The noise of hybrid soliton pulse source (HSPS) with linearly chirped Gaussian apodized fiber Bragg grating is analyzed by couple-mode equations including spontaneous emission noise when the HSPS is mode-locked. Relative intensity noise is calculated using numerical solutions of these equations. It is shown that transform limited pulses are generated over a wide tuning range around the fundamental mode-locking frequency with low spontaneous noise. However, a high noise level affects the operation of device, and therefore transform-limited pulses are not obtainable over a wide tuning range. It is also shown that noise is extremely sensitive to the RF and DC currents, linewidth enhancement factor, gain saturation parameter and spontaneous coupling factor.     

Collective bounce-off phenomenon in139La+Ag(Br) reaction at 1.1 A GeV energy

Out of a total statistics of 896¹³⁹La+Ag(Br) interactions, 128 interactions having multiplicity of target fragments (Z⩾1)⩾8 and projectile fragments (Z⩾2)⩾4 have been selected. They correspond to quasi-peripheral interactions. Azimuthal angle correlation between sources of target fragments (TFs) and projectile fragments (PFs) shows the existence of bounce-off effect. Using data of La+Ag(Br) and⁸⁴Kr+Ag(Br) reactions it is shown that individual helium [Z=2, PFs] and heavier fragment [Z⩾3, PFs] show different emission characteristics. Further, a two prong correlation functionT(Φ _ij ) plotted for heavier fragments and helium fragments separately, indicates the possibility of existence of different physical conditions. This observation is supported by the different momentum widths of helium fragments and heavier fragments. From the momentum width data of Kr+Ag(Br) reactions normalized density comes out to be ≈4.7. Using quasi-elastic kinematics for the bounce-off nuclei, the excitation energy has been computed from the experimental data of flow angles. The strength of bounce-off seems to decrease with the increase of excitation energy or temperature.     

高阶非线性波动方程的有限差分方法

本文研究一类广泛的高阶非线性波动方程组初边值问题的有限差分格式，用离散泛函分析方法和先验估计的技巧得到了有限差分格式的收敛性。     

无失效数据的Bayes和多层Bayes分析

本文推广了文献[6]的结果，对指数分布无失效数据的失效率，给出了Bayes估计、Bayes置信上限以及多层Bayes估计，从而可以得到无失效数据可靠度的估计，最后，结合实际问题进行了计算。     

L1-optimal estimates for a regression type function in R

Let X₁, X₂, …, X_n be random vectors that take values in a compact set in R^d, d ≥ 1. Let Y₁, Y₂, …, Y_n be random variables (“the responses”) which conditionally on X₁ = x₁, …, X_n = x_n are independent with densities f(y | x_i, θ(x_i)), i = 1, …, n. Assuming that θ lives in a sup-norm compact space Θ_q,d of real valued functions, an optimal L₁-consistent estimator of θ is constructed via empirical measures. The rate of convergence of the estimator to the true parameter θ depends on Kolmogorov's entropy of Θ_q,d.