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随机神经网络及其在非线性时间序列中的应用AI 解读

We consider a variant of the conventional neural network model, called the stochastic neural network, that can be used to approximate complex nonlinear stochastic systems. We show how the expectation-maximization algorithm can be used to develop efficient estimation schemes that have much lower computational complexity than those for conventional neural networks. This enables us to carry out model selection procedures, such as the Bayesian information criterion, to choose…

弓头鲸胎儿生长与妊娠期的估计AI 解读

We address estimating fetal growth and gestation for bowhead whales of the Bering, Chukchi, and Beaufort seas stock. This population is subject to a subsistence hunt by Eskimo whale hunters, which is monitored via a quota system established by the International Whaling Commission. Quota determination is assisted by biological information, such as fetal growth and gestation, which is the basis of a population dynamics model used to estimate the annual replacement yield of the…

含相关状态依赖噪声与滤波效应的离子通道隐马尔可夫分析AI 解读

A hidden Markov model that describes ion channel data, including correlated, state-dependent noise and filter characteristics, and a Markov chain Monte Carlo algorithm that enables Bayesian inference under this model are presented. The method provides parameter estimates and an estimate of the noiseless signal. It was tested on simulated data and applied to real recordings to estimate the model parameters. Modeling the noise and filter correctly turned out to be crucial for…

扫描磁阻显微术中磁头灵敏度函数的估计AI 解读

We apply Bayesian image analysis techniques to a problem in a newly developed scanned probe technology that uses commercial magnetoresistive (MR) record and playback heads as probes to sense magnetic fields. This technology can be used for magnetic imaging and for evaluating playback and record processes in magnetic recording. In MR microscopy, an MR head is raster scanned while in physical contact with a magnetic sample (e.g., hard disk media, tape, or fine magnetic…

跨国增长回归中的模型不确定性AI 解读

Abstract We investigate the issue of model uncertainty in cross‐country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is spread widely among many models, suggesting the superiority of BMA over choosing any single model. Out‐of‐sample predictive results support this claim. In contrast to Levine and Renelt ( 1992 ), our results broadly support the more ‘optimistic’ conclusion of Sala‐i‐Martin ( 1997b ), namely that some…

广义矩条件下计算Γ极小极大决策规则的算法AI 解读

We present an algorithm for calculating a $\Gamma$-minimax decision rule, when is given by a finite number of generalized moment conditions. Such a decision rule minimizes the maximum of the integrals of the risk function with respect to all distributions in $\Gamma$. The inner maximization problem is approximated by a sequence of linear programs. This approximation is combined with an elimination technique which quickly reduces the domain of the variables of the outer…

有界正态均值的极大似然估计改进AI 解读

We consider the problem of estimating the mean of a $p$-variate normal distribution with identity covariance matrix when the mean lies in a ball of radius $m$. It follows from general theory that dominating estimators of the maximum likelihood estimator always exist when the loss is squared error. We provide and describe explicit classes of improvements for all problems $(m, p)$. We show that,for small enough $m$, a wide class of estimators, including all Bayes estimators…

This paper is concerned with the Bayesian estimation of nonlinear stochastic differential equations when observations are discretely sampled. The estimation framework relies on the introduction of latent auxiliary data to complete the missing diffusion between each pair of measurements. Tuned Markov chain Monte Carlo (MCMC) methods based on the Metropolis-Hastings algorithm, in conjunction with the Euler-Maruyama discretization scheme, are used to sample the posterior…

含测量误差与工具变量的恩格尔曲线估计：贝叶斯分析AI 解读

In this article, we consider the Bayesian estimation of Engel curves specified as the Working–Leser form with the measurement errors on both the left and the right sides. It is noteworthy that in the Bayesian approach no additional variation data (i.e., instrumental variables) are required in contrast with the non-Bayesian approach. We present the Bayesian estimation procedure in both models without an instrumental variable and with an instrumental variable. We also compare…

利用金融与经济变量预测股票收益的非线性可预测性AI 解读

In a recent article by Qi, neural networks trained by Bayesian regularization were used to predict excess returns on the S&P 500. The article concluded that the switching portfolio based on the recursive neural-network forecasts generates higher accumulated wealth with lower risks than that based on linear regression. Unfortunately, attempts to replicate the results were unsuccessful. Replicated results using the same software, approach and data detailed by Qi indicate that,…

总体规模的贝叶斯分析AI 解读

We consider the problem of estimating the total size of a population from a series of incomplete census data. We observe that inference is typically highly sensitive to the choice of model and we demonstrate how Bayesian model averaging techniques easily overcome this problem. We combine and extend the work of Madigan & York (1997) and Dellaportas & Forster (1999) using reversible jump Markov chain Monte Carlo simulation to calculate posterior model probabilities which can…

一般列联表分析中对数线性模型的先验诱导AI 解读

Log-linear modelling plays an important role in many statistical applications, particularly in the analysis of contingency table data.With the advent of powerful new computational techniques such as reversible jump MCMC, Bayesian analyses of these models, and in particular model selection and averaging, have become feasible. Coupled with this is the desire to construct and use suitably flexible prior structures which allow efficient computation while facilitating prior…

生存模型的后验一致性AI 解读

Ghosh and Ramamoorthi studied posterior consistency for survival models and showed that the posterior was consistent when the prior on the distribution of survival times was the Dirichlet process prior. In this paper,we study posterior consistency of survival models with neutral to the right process priors which include Dirichlet process priors. A set of sufficient conditions for posterior consistency with neutral to the right process priors are given. Interestingly, not all…

后验分布的收敛速率AI 解读

We compute the rate at which the posterior distribution concentrates around the true parameter value. The spaces we work in are quite general and include in finite dimensional cases. The rates are driven by two quantities: the size of the space, as measured by bracketing entropy, and the degree to which the prior concentrates in a small ball around the true parameter. We consider two examples.

经济时间序列表观非线性是否源于结构不稳定？AI 解读

Many modelling issues and policy debates in macroeconomics depend on whether macroeconomic time series are best characterized as linear or nonlinear. If departures from linearity exist, it is important to know whether these are endogenously generated (as in, e.g. a threshold autoregressive model) or whether they merely reflect changing structure over time. In this paper, we discuss a model comparison methodology which addresses these issues. We advocate a Bayesian approach…

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实参数进化蒙特卡洛及其在贝叶斯混合模型中的应用AI 解读

We propose an evolutionary Monte Carlo algorithm to sample from a target distribution with real-valued parameters. The attractive features of the algorithm include the ability to learn from the samples obtained in previous steps and the ability to improve the mixing of a system by sampling along a temperature ladder. The effectiveness of the algorithm is examined through three multimodal examples and Bayesian neural networks. The numerical results confirm that the real-coded…

用于改善图像降噪小波阈值处理的经验贝叶斯方法AI 解读

Wavelet threshold algorithms replace small magnitude wavelet coefficients with zero and keep or shrink the other coefficients. This is basically a local procedure, because wavelet coefficients characterize the local regularity of a function. Although a wavelet transform has decorrelating properties, structures in images, like edges, are never decorrelated completely, and these structures appear in the wavelet coefficients: a classification based on a local criterion-like…

公用电话、停车收费器与自动售货机的最优贝叶斯收款时点AI 解读

Payphones, parking meters, and vending machines illustrate the modern business practice of substituting machinery for manpower. They do not eliminate manual labor completely, because full coin-boxes still must be replaced and vending machines still must be stocked. Deciding when to replace a coin-box is important, with unequal losses resulting from underestimation and overestimation. This article derives optimal methodology for this problem by incorporating collection…

基于纵向标志物贝叶斯层级变点与混合模型的癌症风险筛查AI 解读

The standard approach to early detection of disease with a quantitative marker is to set a population-based fixed reference level for making further individual screening or referral decisions. For many types of disease, including prostate and ovarian cancer, additional information is contained in the subject-specific temporal behavior of the marker, which exhibits a characteristic alteration early in the course of the disease. In this article we derive a Bayesian approach to…

曲线的贝叶斯小波回归及其光谱校准应用AI 解读

Motivated by calibration problems in near-infrared (NIR) spectroscopy, we consider the linear regression setting in which the many predictor variables arise from sampling an essentially continuous curve at equally spaced points and there may be multiple predictands. We tackle this regression problem by calculating the wavelet transforms of the discretized curves, then applying a Bayesian variable selection method using mixture priors to the multivariate regression of…

This article reviews the principle of minimum description length (MDL) for problems of model selection. By viewing statistical modeling as a means of generating descriptions of observed data, the MDL framework discriminates between competing models based on the complexity of each description. This approach began with Kolmogorov's theory of algorithmic complexity, matured in the literature on information theory, and has recently received renewed attention within the…

通过混合实现自适应回归AI 解读

Adaptation over different procedures is of practical importance. Different procedures perform well under different conditions. In many practical situations, it is rather hard to assess which conditions are (approximately) satisfied so as to identify the best procedure for the data at hand. Thus automatic adaptation over various scenarios is desirable. A practically feasible method, named adaptive regression by mixing (ARM), is proposed to convexly combine general candidate…

灵活非线性推断的参数化方法AI 解读

This paper proposes a new framework for determining whether a given relationship is nonlinear, what the nonlinearity looks like, and whether it is adequately described by a particular parametric model. The paper studies a regression or forecasting model of the form yt=μ(xt)+εt where the functional form of μ(⋅) is unknown. We propose viewing μ(⋅) itself as the outcome of a random process. The paper introduces a new stationary random field m(⋅) that generalizes…