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用混合转移分布模型描述时间序列的平坦段、突发与离群值AI 解读

The class of mixture transition distribution (MTD) time series models is extended to general non-Gaussian time series. In these models the conditional distribution of the current observation given the past is a mixture of conditional distributions given each one of the last p observations. They can capture non-Gaussian and nonlinear features such as flat stretches, bursts of activity, outliers changepoints in a single unified model class. They can also represent time series…

预测振荡模式：随机场时空分解方法的综合AI 解读

Spatial-temporal decompositions of climatologic fields have been obtained using a range of techniques, including principal component analysis (PCA) and principal oscillation patterns (POPS). PCA decompositions are forced to be correlated to the original field, but they may not capture interesting aspects of temporal variation. On the other hand, POPS decompositions focus on temporal variation but are not forced to correlate to the field. Here we introduce a hybrid of these…

综合可靠性的概念及其层级贝叶斯估计AI 解读

In this article we introduce the notion of “composite reliability” as a measure of the overall reliability of a collection of heterogeneous but similar items. We then propose a hierarchical Bayes model for estimating the composite reliability of systems whose lifelengths are expressed as binary random variables. Subsequently, we develop an alternative approach for the simultaneous inference about many small but related binomial parameters. We propose a two-stage prior for…

估计通常每日摄入量分布的半参数变换方法AI 解读

The distribution of usual intakes of dietary components is important to individuals formulating food policy and to persons designing nutrition education programs. The usual intake of a dietary component for a person is the long-run average of daily intakes of that component for that person. Because it is impossible to directly observe usual intake for an individual, it is necessary to develop an estimator of the distribution of usual intakes based on a sample of individuals…

时变风险比：建模、假设检验及狼疮性肾炎应用AI 解读

We investigate the association between duration of untreated disease and survival in lupus nephritis, a rare rheumatologic disease. In this case, as in many other studies of survival, a priori considerations suggest that the effect of the predictor on hazard may change with increasing follow-up time. To accommodate such situations, we use regression splines to model the hazard ratio as a flexible function of time. We propose model-based tests of the hypotheses of hazards…

四人家庭收入中位数估计：贝叶斯时间序列方法AI 解读

This article develops a general methodology for small domain estimation based on data from repeated surveys. The results are directly applied to the estimation of median income of four-person families for the 50 states and the District of Columbia. These estimates are needed by the U.S. Department of Health and Human Services (HHS) to formulate its energy assistance program for low income families. The U.S. Bureau of the Census, by an informal agreement, has provided such…

参数事件序列分析：药物使用进程中的性别与族群差异AI 解读

This article introduces novel statistical models for the sequence analysis of events. The models are formulated to analyze occurrence, association, and sequencing among events as an extension of log-linear models. A set of parameters characterizes marginal odds and odds ratios of frequencies summed across sequence patterns for each combination of the occurrence/nonoccurrence of events. These parameters are used for the analysis of the occurrence and association of events.…

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概率与统计教程AI 解读

1. RANDOM VARIABLES AND THEIR DISTRIBUTION Introduction / Sample Distributions / Distributions / Random Variables / Probability Functions and Density Functions / Distribution Functions and Quantiles / Univariate Transformations / Independence 2. EXPECTATION Introduction / Properties of Expectation / Variance / Weak Law of Large Numbers Simulation and the Monte Carlo Method 3. SPECIAL CONTINUOUS MODELS Gamma and Beta Distributions / The Normal Distribution / Normal…

生存分析：实用方法AI 解读

Preface to the First Edition. Preface to the Second Edition. Chapter 1: Introduction and Review of Statistical Concepts. Chapter 2: Survival Curves. Chapter 3: Comparison of Survival Curves. Chapter 4: Parametric Modelling. Chapter 5: Cox's Proportional Hazards Model. Chapter 6: Selecting Variables within a Cox Model. Chapter 7: Extensions of the Cox Model. Chapter 8: Prognostic Indices. Chapter 9: Sample Sizes. Chapter 10: Further Topics. References. Statistical Tables.…

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响应依赖回顾性抽样的最优估计AI 解读

In more conventional analytic surveys, we sample the response variates y through a sampling design that is dependent on the covariate x. The x values are assumed known for all the units in the population. However, contrary to these situations, there are areas of statistical application when the values of the response variable are known for all the individuals but not the values of covariate (for example, in epidemiology and reliability). Here we sample the x values the…

有限混合模型的最小 Hellinger 距离估计AI 解读

Minimum Hellinger distance estimates are considered for finite mixture models when the exact forms of the component densities are unknown in detail but are thought to be close to members of some parametric family. Minimum Hellinger distance estimates are asymptotically efficient if the data come from a member of the parametric family and are robust to certain departures from the parametric family. A new algorithm is introduced that is similar to the EM algorithm a…

一致随机序约束下的生存函数估计AI 解读

If S and T are survival functions for two life distributions, then S is said to be uniformly stochastically smaller than T, denoted by S ≪ T, if θ(x) ≡ S(x)/T(x) is nonincreasing in x on {x: T(x) > 0}. This ordering is transitive. Uniform stochastic ordering (USO) has found important applications in nonparametric accelerated life testing, among other areas. It has been shown that the nonparametric maximum likelihood estimator (NPMLE) of S under USO when T is known is…

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离散持续期与竞争风险模型中风险函数和时变效应的平滑AI 解读

State-space or dynamic approaches to discrete or grouped duration data with competing risks or multiple terminating events allow simultaneous modeling and smooth estimation of hazard functions and time-varying effects in a flexible way. Full Bayesian or posterior mean estimation, using numerical integration techniques or Monte Carlo methods, can become computationally rather demanding or even infeasible for higher dimensions and larger datasets. Therefore, based on previous…

基于重复测量的分位数估计AI 解读

Quantile estimators for a nonparametric components of variance situation are proposed consistency and asymptotic normality are proved. Situations with different numbers of measurements for different subjects are considered. Measurements on separate subjects are assumed to be independent, whereas measurements on the same subject have a fixed dependence. The estimators are obtained by inverting weighted empirical distribution functions. An “optimal” estimator and a simple…

基于频域自助法的传递函数模型拟合检验AI 解读

Transfer function models have been used for modeling the linear dependence between stationary time series and for improving the accuracy of forecasts. This article proposes a method to evaluate the fit of such a model by comparing certain frequency domain functionals of the model with those of the data using a model-based bootstrap algorithm. The method works by checking the ability of the fitted model to reproduce the dynamic relationship and the linear dependence structure…

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借力估计的非齐性分析AI 解读

This article develops a “borrowed strength” methodology for estimating local probability densities in a random field. Under a piecewise stationarity condition similarities between the densities in different regions of the field can be exploited by estimating a global mixture density and imposing the parameter-space support of this borrowed strength estimate on the local estimation problems. The local estimates are then used in an analysis of the homogeneity of the field,…

预测振荡模式：随机场时空分解方法的综合AI 解读

Spatial-temporal decompositions of climatologic fields have been obtained using a range of techniques, including principal component analysis (PCA) and principal oscillation patterns (POPS). PCA decompositions are forced to be correlated to the original field, but they may not capture interesting aspects of temporal variation. On the other hand, POPS decompositions focus on temporal variation but are not forced to correlate to the field. Here we introduce a hybrid of these…