Bias correction for parameter estimates of spatial point process models

When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best.     

Percentage points of the statistics for testing hypotheses on mean vectors of multivariate normal distributions with missing observations

A problem of testing of hypotheses on the mean vector of a multivariate normal distribution with unknown and positive definite covariance matrix is considered when a sample with a special, though not unusual, pattern of missing observations from that population is available. The approximate percentage points of the test statistic are obtained and their accuracy has been checked by comparing them with some exact percentage points which are calculated for complete samples and some special incomplete samples. The approximate percentage points are in good agreement with exact percentage points. The above work is extended to the problem of testing the hypothesis of equality of two mean vectors of two multivariate normal distributions with the same, unknown covariance matrix     

Economic and economic statistical designs for three-level control charts

In some situations, an appropriate quality measure uses three or more discrete levels to classify a product characteristic. For these situations, some control charts have been developed based on statistical criteria regardless of economic considerations. In this paper, we develop economic and economic statistical designs (ESD) for 3-level control charts. We apply the cost model proposed by Costa and Rahim.[Economic design of X charts with variable parameters: the Markov chain approach, J Appl Stat 28 (2001), 875–885] Furthermore, we assume that the length of time that the process remains in control is exponentially distributed which allows us to apply the Markov chain approach for developing the cost model. We apply a genetic algorithm to determine the optimal values of model parameters by minimizing the cost function. A numerical example is provided to illustrate the performance of the proposed models and to compare the cost of the pure economic and ESD for three-level control charts. A sensitivity analysis is also conducted in this numerical example.     

Implementing particle swarm optimization algorithm to estimate the mixture of two Weibull parameters with censored data

We present the maximum likelihood estimation (MLE) via particle swarm optimization (PSO) algorithm to estimate the mixture of two Weibull parameters with complete and multiple censored data. A simulation study is conducted to assess the performance of the MLE via PSO algorithm, quasi-Newton method and expectation-maximization (EM) algorithm for different parameter settings and sample sizes in both uncensored and censored cases. The simulation results showed that the PSO algorithm outperforms the quasi-Newton method and the EM algorithm in most cases regarding bias and root mean square errors. Two numerical examples are used to demonstrate the performance of our proposed method.     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.     

论夜间搜查——从两则案例谈起

由于我国《刑事诉讼法》对搜查的时间未作规定,导致司法实践中夜间搜查频繁出现。夜间搜查很容易侵犯被搜查人和与其同住的人的隐私权和生活安宁权,给其造成伤害,司法实践中也确实发生了因夜间搜查而把人吓病的案例。因此,我国在再次修改《刑事诉讼法》时应规定禁止夜间搜查。当然,在保护公民隐私权和生活安宁权的同时,也要兼顾打击犯罪的需要,法律可以设置一些禁止夜间搜查的例外。     

Do resources of network members help in help seeking? Social capital and health information search

Does social capital as resources of network members affect health information search? Analyzing data from the 2004 General Social Survey in the United States, this study measures two social capital indicators (average education of network members and proportion of network members with a high school degree or higher) using the name generator. Most results are consistent using those two indicators. Both indicators are positively associated with frequency of health information seeking and seekers’ frequency of use of two sources (friends or relatives and the Internet). Also average education of network members is positively associated with seekers’ diversity of used sources and frequency of consultation with medical professionals. But neither indicator is associated with seekers’ frequency of use of other four sources (health-related magazines or newsletters, general magazines, daily newspapers, and radio or television programs). The findings demonstrate the theoretical utility of social capital in the social dynamics of medical help-seeking.     

Attachment and Self‐Efficacy in Career Search Activities: A Structural Model

The author integrated attachment theory with social cognitive career theory (SCCT) to examine how attachment styles influence the career search self‐efficacy activities of interviewing, networking, job searching, and personal exploration. Using an undergraduate sample (N = 275, 81% women), the author tested a structural model. Results indicated that anxious attachment style was negatively related to interviewing self‐efficacy, whereas avoidant attachment style was negatively related to networking, job searching, and personal exploration self‐efficacy. Theoretical implications based on these findings provide support for an integrative model of attachment theory with SCCT. Career counselors are encouraged to consider clients’ attachment styles when working with individuals who are searching for employment. To help address the limitations of the study, future researchers could test the applicability of the current model with a more diverse sample.     

Bayesian inference under progressive type-I interval censoring

Bayesian estimation for population parameter under progressive type-I interval censoring is studied via Markov Chain Monte Carlo (MCMC) simulation. Two competitive statistical models, generalized exponential and Weibull distributions for modeling a real data set containing 112 patients with plasma cell myeloma, are studied for illustration. In model selection, a novel Bayesian procedure which involves a mixture model is proposed. Then the mix proportion is estimated through MCMC and used as the model selection criterion.     

Optimal determination of the parameters of some biased estimators using genetic algorithm

In this paper, some new algorithms for estimating the biasing parameters of the ridge, Liu and two-parameter estimators are introduced with the help of genetic algorithm (GA). The proposed algorithms are based on minimizing some statistical measures such as mean square error (MSE), mean absolute error (MAE) and mean absolute prediction error (MAPE). At the same time, the new algorithms allow one to keep the condition number and variance inflation factors to be less than or equal to ten by means of the GA. A numerical example is presented to show the utility of the new algorithms. In addition, an extensive Monte Carlo experiment is conducted. The numerical findings prove that the proposed algorithms enable to eliminate the problem of multicollinearity and minimize the MSE, MAE and MAPE.