面向网络营销企业的营销信号选择博弈分析

如何通过营销信号来降低电子市场逆向选择风险是影响网络营销企业业绩的重要因素.本文以两家企业垄断市场为例,建立了企业信号传递博弈模型.通过对分离均衡与混同均衡存在条件的分析,讨论了信号传递成本以及不同消费者群体所占比例对企业营销信号决策的影响.分析结果有助于网络营销企业在电子市场中选择营销信号.     

利用伪随机信号系统辨识钻柱系统

用白噪声信号作为输入信号对钻柱系统脉冲响应进行辨识。研究了伪随机信号的特征及伪随机信号产生的方法,得出了用伪随机信号代替白噪声信号辨识钻柱系统脉冲响应的结论。结合输入信号和输出信号,利用钻柱系统的脉冲响应,讨论了钻柱的临界转速、钻柱共振、钻柱与井壁之间的相互作用、所钻地层岩性等钻井工程问题。     

Robustness to non-normality and autocorrelation of individuals control charts

This paper studies the effects of non-normality and autocorrelation on the performances of various individuals control charts for monitoring the process mean and/or variance. The traditional Shewhart X chart and moving range (MR) chart are investigated as well as several types of exponentially weighted moving average (EWMA) charts and combinations of control charts involving these EWMA charts. It is shown that the combination of the X and MR charts will not detect small and moderate parameter shifts as fast as combinations involving the EWMA charts, and that the performana of the X and MR charts is very sensitive to the normality assumption. It is also shown that certain combinations of EWMA charts can be designed to be robust to non-normality and very effective at detecting small and moderate shifts in the process mean and/or variance. Although autocorrelation can have a significant effect on the in-control performances of these combinations of EWMA charts, their relative out-of-control performances under independence are generally maintained for low to moderate levels of autocorrelation.     

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.     

The social as signal in the body of chromatin

Human social interactions and material cultures are increasingly understood as biologically consequent environmental signals. Within the explanatory framework of epigenetics, such signals become biologically inscribed when transduced into bodies as persistent patterns of molecular conformation. In the life sciences, persistence of the social as the biological is understood as establishment of gene expression potentials, physiological changes, or epigenetic memories. How did the social become interchangeable with the environmental? When did both become scientifically graspable as signals? This article recounts the history of how hormone biologists came to think in terms of signal transduction in the late 1960s. This cybernetic legacy is important for understanding the ‘environmental turn’ of epigenetics. To understand the social as signal in the present moment – a post-cybernetic rather than post-genomic moment – the theory of the signal must itself be excavated and analysed.     

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

Summary.  Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive regression models, latent Gaussian models , where the latent field is Gaussian, controlled by a few hyperparameters and with non-Gaussian response variables. The posterior marginals are not available in closed form owing to the non-Gaussian response variables. For such models, Markov chain Monte Carlo methods can be implemented, but they are not without problems, in terms of both convergence and computational time. In some practical applications, the extent of these problems is such that Markov chain Monte Carlo sampling is simply not an appropriate tool for routine analysis. We show that, by using an integrated nested Laplace approximation and its simplified version, we can directly compute very accurate approximations to the posterior marginals. The main benefit of these approximations is computational: where Markov chain Monte Carlo algorithms need hours or days to run, our approximations provide more precise estimates in seconds or minutes. Another advantage with our approach is its generality, which makes it possible to perform Bayesian analysis in an automatic, streamlined way, and to compute model comparison criteria and various predictive measures so that models can be compared and the model under study can be challenged.     

The Peasant World in the Discourse of Generational Sorrow

This article spells out the methodological considerations and various procedural and methodological subtleties developed over the author's quarter century of sociological field studies of Russia's peasant worlds. Particular attention is paid to “voices from below”—peasant discursive formats that capture, in natural and undiluted form, the evolution of peasant practices constituting the core of everyday life. In particular, the phenomenon of generational sorrow and a special chronological nostalgia that functions as a “social gyroscope” is identified and discursively captured. This phenomenon is noteworthy and useful for its ability to retain a record of the productively longed for past in a rural community's collective memory and thereby influence new peasant worlds taking shape today.     

Statistical analysis of dependent competing risks model in accelerated life testing under progressively hybrid censoring using copula function

This article considers statistical analysis of dependent competing risks model from Weibull distribution in accelerated life testing, in which copula function is used to examine the dependence structure between competing failure modes. We derive the maximum likelihood estimates, the approximate, and Bootstrap confidence intervals of the parameters. The effects of different dependence structures on the estimates of parameters are investigated. The simulation is given to compare the performance of the estimates when the competing failure modes are dependent with those when the failure modes are independent. Finally, one dataset was used for illustrative purpose in conclusion.     

Monitoring the coefficient of variation using a variable sample size and sampling interval control chart

This article proposes a CV chart by using the variable sample size and sampling interval (VSSI) feature to improve the performance of the basic CV chart, for detecting small and moderate shifts in the CV. The proposed VSSI CV chart is designed by allowing the sample size and the sampling interval to vary. The VSSI CV chart's statistical performance is measured by using the average time to signal (ATS) and expected average time to signal (EATS) criteria and is compared with that of existing CV charts. The Markov chain approach is employed in the design of the chart.     

A direct procedure for monitoring the coefficient of variation using a variable sample size scheme

A variable sample size (VSS) scheme directly monitoring the coefficient of variation (CV), instead of monitoring the transformed statistics, is proposed. Optimal chart parameters are computed based on two criteria: (i) minimizing the out-of-control ARL (ARL₁) and (ii) minimizing the out-of-control ASS (ASS₁). Then the performances are compared between these two criteria. The advantages of the proposed chart over the VSS chart based on the transformed statistics in the existing literature are: the former (i) provides an easier alternative as no transformation is involved and (ii) requires less number of observations to detect a shift when ASS₁ is minimized.