缺少投影角度与时变物体断层重建的外推恢复正弦图方法

本文针对缺少投影角度及物体时变这两类缺损投影数据问题，在分析了限宽间区域及限频域图像的雷当变换的若干性质基础上，分别导出基于最小均方误差准则的外推公式，从而得到完整的正弦图的最佳估计，基于这一外推所得的正弦图，可以利用传统的断层重建方法对物体进行重建，本文给出了外推公式的推导过程有其求解的迭代算法，计算机模拟结果显示了这一技术的有效性。     

Logical operators of some statistical computing packages and missing values

When using statistical computer packages in general, we rely on the results they produce. We are aware that numerical approximations are made and trust that the best algorithms are chosen to do them. Most manuals give us instructions about precision of calculations and some report how missing values are administered. What we are unaware of is that some packages can invent results when creating atomic formulas and compounding complex formulas out of atomic ones, what inflates sample sizes, and possibly leads us to incorrect statistical decisions. Two simple indicator variables, with missing values positioned so the results are always missing values, were tested as numerical, as logical and as character variables, by compounding them through connective ‘and’ (&) and ‘or’ (|) to form new indicator variables. The results show that one of the three very known packages does not, statistically, correctly handle missing values, and the three make atomic formulas out of character variables assigning the value false (0) for missing value, what can be said an statistical error. The conclusion is that statisticians and users of statistics must be aware of the capabilities of logically operating missing values of the statistical packages they use, otherwise wrong statistical decisions can be made. And that programmers of statistical packages should correct their algorithms in order to not permit their packages invent non-existing values.     

Covariance miss-specification and the local influence approach in sensitivity analyses of longitudinal data with drop-outs

Our work examines the performance of proposed local influence diagnostics applied to multivariate normal longitudinal data with drop-outs: these diagnostics prove to be ambiguous as they are sensitive not only to the presence of anomalous records, as intended, but also, unfortunately, to the misspecification of the longitudinal covariance structure of the response. We suggest an unambiguous index for detecting covariance misspecification, and recommend that an analyst use this index first to confirm that the covariance structure is well specified before attempting to interpret the influence diagnostics.     

SYMMETRIC STABLE SEQUENCES WITH MISSING OBSERVATIONS

Abstract. A procedure for evaluating optimal linear estimates of missing values in the minimum dispersion sense is proposed for stationary symmetric stable processes. Analytical expressions for the estimates are obtained for the autoregressive moving-average process and it is shown that the finite variance setting results are special cases. Cases of one and more than one missing value are considered.     

Model selection for zero-inflated regression with missing covariates

Count data are widely existed in the fields of medical trials, public health, surveys and environmental studies. In analyzing count data, it is important to find out whether the zero-inflation exists or not and how to select the most suitable model. However, the classic AIC criterion for model selection is invalid when the observations are missing. In this paper, we develop a new model selection criterion in line with AIC for the zero-inflated regression models with missing covariates. This method is a modified version of Monte Carlo EM algorithm which is based on the data augmentation scheme. One of the main attractions of this new method is that it is applicable for comparison of candidate models regardless of whether there are missing data or not. What is more, it is very simple to compute as it is just a by-product of Monte Carlo EM algorithm when the estimations of parameters are obtained. A simulation study and a real example are used to illustrate the proposed methodologies.     

Determining the number of principal components for best reconstruction

A well-defined variance of reconstruction error (VRE) is proposed to determine the number of principal components in a PCA model for best reconstruction. Unlike most other methods in the literature, this proposed VRE method has a guaranteed minimum over the number of PC's corresponding to the best reconstruction. Therefore, it avoids the arbitrariness of other methods with monotonic indices. The VRE can also be used to remove variables that are little correlated with others and cannot be reliably reconstructed from the correlation-based PCA model. The effectiveness of this method is demonstrated with a simulated process.     

节流式差压流量计为何仍有优势

在系统分析涡街流量计所具有优点的基础上，具体阐述了涡街流量计的耐振性能等。同时也指出了它所存在的缺点，并相应地给出其新的改进，指出在选择合适的流量计时应扬其所长，避其所短。为流量计的选型提供了可靠的参考价值。     

Mixed model-based inference in geoadditive hazard regression for interval-censored survival times

Mixed model-based estimation of additive or geoadditive regression models has become popular throughout recent years. It provides a unified and modular framework that facilitates joint estimation of nonparametric covariate effects and the corresponding smoothing parameters. Therefore, extensions of mixed model-based inference to a Cox-type regression model for the hazard rate are considered, allowing for a combination of general censoring schemes for the survival times and a flexible, geoadditive predictor. In particular, the proposed methodology allows for arbitrary combinations of right, left, and interval censoring as well as left truncation. The geoadditive predictor comprises time-varying effects, nonparametric effects of continuous covariates, spatial effects, and potentially a number of extensions such as cluster-specific frailties or interaction surfaces. In addition, all covariates are allowed to be piecewise constant time-varying. Nonlinear and time-varying effects as well as the baseline hazard rate are modeled by penalized splines. Spatial effects can be included based on either Markov random fields or stationary Gaussian random fields. Estimation is based on a reparametrization of the model as a variance component mixed model. The variance parameters, corresponding to inverse smoothing parameters, can then be determined using an approximate marginal likelihood approach. An analysis on childhood mortality in Nigeria serves as an application, where the interval censoring framework additionally allows to deal with the problem of heaped survival times. The effect of ignoring the impact of interval-censored observations is investigated in a simulation study.     

光栅衍射谱线产生缺级的条件

本文对光栅衍射谱线产生缺级的条件进行了讨论，澄清了某些教科书中不确切的叙述。     

Parameter estimation with scarce measurements

In this paper, the problems of parameter estimation are addressed for systems with scarce measurements. A gradient-based algorithm is derived to estimate the parameters of the input–output representation with scarce measurements, and the convergence properties of the parameter estimation and unavailable output estimation are established using the Kronecker lemma and the deterministic version of the martingale convergence theorem. Finally, an example is provided to demonstrate the effectiveness of the proposed algorithm.