On Some Applications of Poisson Point Processes

Poisson point processes play important role in various domains of Probability Theory and Mathematical Statistics. In this article, we investigate only two applications of Poisson point processes: a generated white noise problem and parameters estimation problem. This work continues the investigations started in paper Egorov and Kondybaev (2009 Egorov , V. A. , Kondybaev , N. S. ( 2009 ). On the estimation of a signal covered by background om Poisson noise . Methods and programs of data processing 4 : 75 – 81 . [Google Scholar]).     

Least Squares Consistent Estimates for Arbitrary Regression Functions Over an Abstract Space

In this article, we propose a new approach to sieve estimation for a general regression function when the dimension of the finite dimensional subspaces is a random quantity depending on the values of the observations.

The technique is introduced with the help of a simulation study on a functional linear model under extremely mild assumptions.

A sketch of the proof concerning the main statements is then given in the more general case when the regression function is not necessarily linear.     

A Small Area Predictor under Area-Level Linear Mixed Models with Restrictions

A calibrated small area predictor based on an area-level linear mixed model with restrictions is proposed. It is showed that such restricted predictor, which guarantees the concordance between the small area estimates and a known estimate at the aggregate level, is the best linear unbiased predictor. The mean squared prediction error of the calibrated predictor is discussed. Further, a restricted predictor under a particular time-series and cross-sectional model is presented. Within a simulation study based on real data collected from a longitudinal survey conducted by a national statistical office, the proposed estimator is compared with other competitive restricted and non-restricted predictors.     

Bayesian analysis of skew-normal independent linear mixed models with heterogeneity in the random-effects population

We present a new class of models to fit longitudinal data, obtained with a suitable modification of the classical linear mixed-effects model. For each sample unit, the joint distribution of the random effect and the random error is a finite mixture of scale mixtures of multivariate skew-normal distributions. This extension allows us to model the data in a more flexible way, taking into account skewness, multimodality and discrepant observations at the same time. The scale mixtures of skew-normal form an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal, skew-Student-t, skew-slash and the skew-contaminated normal distributions as special cases, being a flexible alternative to the use of the corresponding symmetric distributions in this type of models. A simple efficient MCMC Gibbs-type algorithm for posterior Bayesian inference is employed. In order to illustrate the usefulness of the proposed methodology, two artificial and two real data sets are analyzed.     

Efficient estimation for incomplete multivariate data

We review the Fisher scoring and EM algorithms for incomplete multivariate data from an estimating function point of view, and examine the corresponding quasi-score functions under second-moment assumptions. A bias-corrected REML-type estimator for the covariance matrix is derived, and the Fisher, Godambe and empirical sandwich information matrices are compared. We make a numerical investigation of the two algorithms, and compare with a hybrid algorithm, where Fisher scoring is used for the mean vector and the EM algorithm for the covariance matrix.     

Convolution power kernels for density estimation

We propose a new type of non-parametric density estimators fitted to random variables with lower or upper-bounded support. To illustrate the method, we focus on nonnegative random variables. The estimators are constructed using kernels which are densities of empirical means of m i.i.d. nonnegative random variables with expectation 1. The exponent m   plays the role of the bandwidth. We study the pointwise mean square error and propose a pointwise adaptive estimator. The risk of the adaptive estimator satisfies an almost oracle inequality. A noteworthy result is that the adaptive rate is in correspondence with the smoothness properties of the unknown density as a function on (0,+∞)$(0,+\infty )$. The adaptive estimators are illustrated on simulated data. We compare our approach with the classical kernel estimators.     

Estimating Age: College Males Versus Convicted Male Child Sex Offenders

Two samples, male college students and convicted male child sex offenders, are compared on their abilities to accurately estimate the age group of a series of photographs of a sole female ranging in age from 11 to 29. Both samples tend to overestimate the age group of the subject photos, and no significant difference was found between college students and convicted child sex offenders in their ability to estimate the age of females. Both groups are compared demographically, and only limited differences were found. The implications are discussed in regard to theory and prevention of child sexual abuse.     

基于DSGE模型的利率传导机制研究

动态随机一般均衡模型对中国的经济数据拟合较好,可用来分析中国的经济问题;利率作为中国货币政策的中介目标是适宜的,泰勒规则可以用来指导中国的货币政策实践;利率冲击通过影响资本投资价值进而投资而对产出产生影响,消费的传导作用相对较小。     

The Role of Contraceptive Supply and Demand in Mexican Fertility Decline: Evidence from a Microdemographic Study

This paper uses retrospective life history data to assess the impact of family planning services on contraceptive use in a rural Mexican township. Between 1960 and 1990 contraceptive use rose and fertility declined dramatically. Both contraceptive supply and demand factors were influential in these trends. The start of the government-sponsored family planning programme in the late 1970s was associated with a sharp rise in female sterilization and use of the IUD. However, once we controlled for the changing socio-economic and demographic characteristics of the sample, the presence of family planning services had no significant effect on the likelihood that women used modern reversible methods compared to traditional methods. Men and women expressed concerns about the safety of modern methods such as the pill and the IUD. Efforts to increase modern contraceptive use should place greater emphasis on communicating the safety of these methods and improving the quality of services.     

The measurement of historical trends in fetal mortality in England and Wales

This paper critically discusses recent attempts to estimate long-term trends in the stillbirth rate for England and Wales. It assesses the available historical evidence for the level of late-fetal mortality, drawing especially on examples from Norway, Sweden, and Denmark. A theoretical fetal–infant life table for a high-mortality population is also outlined as a means of analysing the relationship between segments of the conception-to-first-birthday mortality curve. Finally, new estimates of the stillbirth rate for England and Wales are proposed, based on variations in the early neonatal and maternal mortality rates during the 1930s. These estimates are substantially lower than the earlier estimates and are more in keeping with the available evidence from northern Europe. The implications of the revised estimates for interpretations of historical changes in mortality patterns are also considered.