Bayes Hilbert Spaces

A Bayes linear space is a linear space of equivalence classes of proportional σ‐finite measures, including probability measures. Measures are identified with their density functions. Addition is given by Bayes' rule and substraction by Radon–Nikodym derivatives. The present contribution shows the subspace of square‐log‐integrable densities to be a Hilbert space, which can include probability and infinite measures, measures on the whole real line or discrete measures. It extends the ideas from the Hilbert space of densities on a finite support towards Hilbert spaces on general measure spaces. It is also a generalisation of the Euclidean structure of the simplex, the sample space of random compositions. In this framework, basic notions of mathematical statistics get a simple algebraic interpretation. A key tool is the centred‐log‐ratio transformation, a generalization of that used in compositional data analysis, which maps the Hilbert space of measures into a subspace of square‐integrable functions. As a consequence of this structure, distances between densities, orthonormal bases, and Fourier series representing measures become available. As an application, Fourier series of normal distributions and distances between them are derived, and an example related to grain size distributions is presented. The geometry of the sample space of random compositions, known as Aitchison geometry of the simplex, is obtained as a particular case of the Hilbert space when the measures have discrete and finite support.     

MATLAB在傅里叶变换教学中的应用

针对《信号与系统》课程中傅里叶变换知识具有抽象度高、难于理解的特点,利用MATLAB强大的信号处理功能,结合傅里叶变换中的典型非周期信号、奇异函数、周期信号的内容,实现了课程教学中的各种运算、变换的直观演示.加深了学生对时域和频域概念、分析方法的理解,极大地改善了教学效果.     

Tail exponent estimation via broadband log density-quantile regression

Heavy tail probability distributions are important in many scientific disciplines such as hydrology, geology, and physics and therefore feature heavily in statistical practice. Rather than specifying a family of heavy-tailed distributions for a given application, it is more common to use a nonparametric approach, where the distributions are classified according to the tail behavior. Through the use of the logarithm of Parzen's density-quantile function, this work proposes a consistent, flexible estimator of the tail exponent. The approach we develop is based on a Fourier series estimator and allows for separate estimates of the left and right tail exponents. The theoretical properties for the tail exponent estimator are determined, and we also provide some results of independent interest that may be used to establish weak convergence of stochastic processes. We assess the practical performance of the method by exploring its finite sample properties in simulation studies. The overall performance is competitive with classical tail index estimators, and, in contrast, with these our method obtains somewhat better results in the case of lighter heavy-tailed distributions.     

Instrumental Variable Estimation of Nonlinear Errors‐in‐Variables Models

This paper establishes that instruments enable the identification of nonparametric regression models in the presence of measurement error by providing a closed form solution for the regression function in terms of Fourier transforms of conditional expectations of observable variables. For parametrically specified regression functions, we propose a root n consistent and asymptotically normal estimator that takes the familiar form of a generalized method of moments estimator with a plugged‐in nonparametric kernel density estimate. Both the identification and the estimation methodologies rely on Fourier analysis and on the theory of generalized functions. The finite‐sample properties of the estimator are investigated through Monte Carlo simulations.     

带传动装置的振动研究

对带传动装置的振动进行了实验研究,测试了在不同带轮偏心配置及不同转速下带轮的纵向振动,发现带轮偏心造成的离心力和由变频调速 引起电机的随时间震荡的电磁转矩是造成振动的主要原因。     

相位舍位对DDS谱分布的影响

采用严格的信号分析方法，运用离散傅里叶变换（ＤＦＴ）和傅里叶变换（ＦＴ）详细推导了理想状态和相位舍位条件下直接数字频率合成器（ＤＤＳ）的频谱分布规律。所得到的理论推算结果与目前公认的结果一致，这对实际的ＤＤＳ系统设计有着极大的参考价值     

A model of the age patterns of births by parity in natural fertility populations

This research develops a convolution model to express the age patterns of fertility at each birth order in natural fertility populations in terms of six parameters, directly representing the proximate determinants of fertility, and a series of parity level indicators. The parity level indicators at each birth order are simply the proportions of women in a cohort who will eventually have births at each birth order it the age‐related fecundity decline is controlled. The Coale‐McNeil nuptiality model is adopted to represent the age pattern of first marriage rates and the natural fertility schedule employed in the Coale‐Trussell fertility model is incorporated to adjust age effects. The fast Fourier transform is used in solving the model numerically. It proves that the model is able to provide excellent fits to fertility for rural Chinese women in the 1950s.     

我国的通货膨胀与名义利率粘性:长期与短期费雪效应

弱费雪效应和名义利率粘性是货币政策有效的前提。本文使用傅里叶变换处理实际利率的时变性，扩展协整模型用以考察长期的费雪效应，并建立门限误差修正模型区分长期和短期的费雪效应，刻画名义利率短期的动态调整特征。基于我国1990年1月至2017年12月的月度数据研究发现：（1）我国名义利率和通货膨胀之间存在长期的弱费雪效应；（2）名义利率的短期动态调整特征存在显著的双重门限效应，在名义利率过度高于均衡值时会出现显著而快速的调整，而当名义利率低于均衡值或处于中间机制时，均没有发现显著的调整，即名义利率存在粘性。研究结果表明：当前阶段数量型货币政策在我国依然有效，因而存在综合使用数量型货币政策和价格型货币政策的空间。     

On the History of the Correction for Grouping, 1873–1922

The correction for grouping is a sum of two terms, the first depending on the length of the grouping interval, the second being a periodic function of the position. Thiele (1873) studied the second term, but missed the first. Sheppard (1898) studied the first term, but missed the second. Bruns (1906) derived the first term as the aperiodic term of a Fourier series and the second as the sum of the periodic terms. He found the correction to the coefficients of the Gram–Charlier series and proved that the second term is negligible for a grouped normal distribution with at least eight groups. Independently, Fisher (1922) used the same method to derive the correction to the moments. For the normal distribution with a grouping interval less than the standard deviation Fisher proved that the second term is negligible compared with the first and with the standard error of the first four moments. Moreover, he proved that the estimates of the mean and the standard deviation obtained by the method of moments for a grouped sample with Sheppard's corrections have nearly the same variances as the maximum likelihood estimates, thus providing a new and compelling reason for using Sheppard's corrections.