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疾病风险因素的汇总数据研究AI 解读

Statistical methods are proposed for estimating relative rate parameters, based on estimated disease rates and covariate data from random samples of individuals from each of several cohorts. A random effects model is used to derive mean and variance models for estimated disease rates. Estimating equations for relative rate parameters are then developed by replacing cohort covariate averages by corresponding sample averages. The asymptotic distribution of regression parameter…

含测量误差的定量风险因素最优序贯筛查准则AI 解读

Any screening program based on a quantitative risk factor has the objective of identifying individuals at high risk of disease. When the risk factor varies within individuals over time or is subject to measurement error, repeat measurements should aid risk assessment. This article presents statistical guidelines for sequential screening based on measurements accumulated over time. The aim for each subject is to decide whether (a) risk is sufficiently low that screening can…

疾病风险因素的聚合数据研究AI 解读

Statistical methods are proposed for estimating relative rate parameters, based on estimated disease rates and covariate data from random samples of individuals from each of several cohorts. A random effects model is used to derive mean and variance models for estimated disease rates. Estimating equations for relative rate parameters are then developed by replacing cohort covariate averages by corresponding sample averages. The asymptotic distribution of regression parameter…

重新审视股票预期收益的横截面AI 解读

ABSTRACT Our examination of the cross‐section of expected returns reveals economically and statistically significant compensation (about 6 to 9 percent per annum) for beta risk when betas are estimated from time‐series regressions of annual portfolio returns on the annual return on the equally weighted market index. The relation between book‐to‐market equity and returns is weaker and less consistent than that in Fama and French (1992). We conjecture that past book‐to‐market…

协整系统中共同长记忆成分的估计AI 解读

The study of cointegration in large systems requires a reduction of their dimensionality. To achieve this, we propose to obtain the I(1) common factors in every subsystem and then analyze cointegration among them. In this article, a new way of estimating common long-memory components of a cointegrated system is proposed. The identification of these I(1) common factors is achieved by imposing that they be linear combinations of the original variables Xt , and that the…

用最小加性主成分分析加性依赖与曲线共线性AI 解读

Additive principal components are a nonlinear generalization of linear principal components. Their distinguishing feature is that linear forms $\sum_ia_i X_i$ are replaced with additive functions $\sum_i\phi_i(X_i)$. A considerable amount of flexibility for fitting data is gained when linear methods are replaced with additive ones. Our interest is in the smallest principal components, which is somewhat uncommon. Smallest additive principal components amount to data…

基于似然模型的半参数回归AI 解读

A weighted likelihood is used to estimate the parameters in a semiparametric model involving two covariates and allowing an association between the covariates. The development is for arbitrary but specified densities of the observations. The estimators are consistent and asymptotically normal. Hypothesis testing of the parametric component can be performed using a Wald test. Simulations and analysis of data with Bernoulli observations demonstrate the estimators' application.…

多个预测目标的联合连续统回归AI 解读

This article generalizes continuum regression (CR) in the hope that regressors “jointly constructed” for several predictands might improve on the separate prediction of individual predictands. The generalization developed is a mixture of principal components regression and de Jong's modification of partial least squares for multiple predictands. The balance of ingredients can be chosen by cross-validation, as can the number of regressors constructed. The new method has been…

基于似然模型的半参数回归AI 解读

A weighted likelihood is used to estimate the parameters in a semiparametric model involving two covariates and allowing an association between the covariates. The development is for arbitrary but specified densities of the observations. The estimators are consistent and asymptotically normal. Hypothesis testing of the parametric component can be performed using a Wald test. Simulations and analysis of data with Bernoulli observations demonstrate the estimators' application.…

相似曲线数据中共同回归函数的非参数估计AI 解读

The paper is concerned with data from a collection of different, but related, regression curves $(m_j0_{j = 1}, \ldots, N, N \gg 1$. In statistical practice, analysis of such data is most frequently based on low-dimensional linear models. It is then assumed that each regression curve $m_j$ is a linear combination of a small number $L \ll N$ of common functions $g_1, \ldots, g_L$k. For example, if all $m_j$'s are straight lines, this holds with $L = 2, g_1 \equiv 1$ and $g_2(x) = x$…

用多重插补评估血压的长期趋势AI 解读

The National Center for Health Statistics makes available data from three national health evaluation surveys that it has conducted since 1960: NHES I (1960-1962), NHANES I (1971-1975), and NHANES II (1976-1980). There has been considerable interest in using these data to assess secular trends in cardiovascular risk factors such as blood pressure (BP). Unfortunately, underlying trends in BP are confounded with trends in physician treatment of hypertension over the same…

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评估血压长期趋势：多重插补方法AI 解读

The National Center for Health Statistics makes available data from three national health evaluation surveys that it has conducted since 1960: NHES I (1960-1962), NHANES I (1971-1975), and NHANES II (1976-1980). There has been considerable interest in using these data to assess secular trends in cardiovascular risk factors such as blood pressure (BP). Unfortunately, underlying trends in BP are confounded with trends in physician treatment of hypertension over the same…

复 Bingham 分布与形状分析AI 解读

SUMMARY A complex version of the Bingham distribution is defined on the unit complex sphere in Ck. Various statistical properties, including asymptotic normality under high concentration, are derived. Symmetries in the distribution make it a natural tool for the analysis of the shape of landmark data in two dimensions. Strengths and weaknesses of this approach are investigated. Links and contrasts with Bookstein co-ordinates are discussed. A hybrid approach to principal…

波动率与各国股票市场之间的联系AI 解读

The authors attempt to account for the covariances between stock markets and to assess their integration. They estimate a factor model for sixteen national stock market returns whose volatility is induced by changing volatility in the factors. Unanticipated returns depend on innovations in economic variables and 'unobservable' factors. Assets risk premia are linear combinations of the factors risk premia. The authors find that idiosyncratic risk is priced and the 'price of…

仅少数成分相关时的预测方法比较AI 解读

We consider prediction in a multiple regression model where we also look on the explanatory variables as random. If the number of explanatory variables is large, then the common least squares multiple regression solution may not be the best one. We give a methodology for comparing certain alternative prediction methods by asymptotic calculations and perform such a comparisons for four specific methods. The results indicate that none of these methods dominates the others, and…

偏最小二乘法的一种解释AI 解读

Univariate partial least squares (PLS) is a method of modeling relationships between a Y variable and other explanatory variables. It may be used with any number of explanatory variables, even far more than the number of observations. A simple interpretation is given that shows the method to be a straightforward and reasonable way of forming prediction equations. Its relationship to multivariate PLS, in which there are two or more Y variables, is examined, and an example is…

近似因子模型中因子个数的检验AI 解读

ABSTRACT An important issue in applications of multifactor models of asset returns is the appropriate number of factors. Most extant tests for the number of factors are valid only for strict factor models, in which diversifiable returns are uncorrelated across assets. In this paper we develop a test statistic to determine the number of factors in an approximate factor model of asset returns, which does not require that diversifiable components of returns be uncorrelated…

稳健奇异值分解：投影寻踪的新方法AI 解读

Robust location and covariance estimators are developed via general M estimation for covariance matrix eigenvectors and eigenvalues. The solution to this GM estimation problem is obtained by transforming it into a series of robust regression problems based on a new algorithm for the singular value decomposition. It is shown here that the singular value decomposition can be represented as an iteration of two steps: a least squares regression fit of the data matrix followed by…

稳健奇异值分解：投影寻踪的新方法AI 解读

Robust location and covariance estimators are developed via general M estimation for covariance matrix eigenvectors and eigenvalues. The solution to this GM estimation problem is obtained by transforming it into a series of robust regression problems based on a new algorithm for the singular value decomposition. It is shown here that the singular value decomposition can be represented as an iteration of two steps: a least squares regression fit of the data matrix followed by…

将部分拟合优度统计量修改为渐近正态零分布AI 解读

SUMMARY The Cramér-von Mises class of test statistics for the one-sample goodness-of-fit problem is based on the weighted L2-distance of the distribution from its empirical counterpart. It is well known that the root π standardized norm has a degenerate limiting distribution under the null hypothesis, and the π standardized norm has a nondegenerate limiting distribution that is not normal and depends on identifying the principal components for every weight function. Usually…

利用共轭梯度加速 EM 算法AI 解读

The EM algorithm is a very popular and widely applicable algorithm for the computation of maximum likelihood estimates. Although its implementation is generally simple, the EM algorithm often exhibits slow convergence and is costly in some areas of application. Past attempts to accelerate the EM algorithm have most commonly been based on some form of Aitken acceleration. Here we propose an alternative method based on conjugate gradients. The key, as we show, is that the EM…

图形辅助回归：应用统计的进阶课程AI 解读

1. Variable Distributions 2. Bivariate Regression Analysis 3. Basics of Multiple Regression 4. Regression Criticism 5. Fitting Curves 6. Robust Regressions 7. Logit Regression 8. Principle Components and Factor Analysis

使零假设极限分布渐近正态的拟合优度统计量修正AI 解读

SUMMARY The Cramér-von Mises class of test statistics for the one-sample goodness-of-fit problem is based on the weighted L2-distance of the distribution from its empirical counterpart. It is well known that the root π standardized norm has a degenerate limiting distribution under the null hypothesis, and the π standardized norm has a nondegenerate limiting distribution that is not normal and depends on identifying the principal components for every weight function. Usually…