Monitoring the mean of autocorrelated observations with one generally weighted moving average control chart

Traditionally, using a control chart to monitor a process assumes that process observations are normally and independently distributed. In fact, for many processes, products are either connected or autocorrelated and, consequently, obtained observations are autocorrelative rather than independent. In this scenario, applying an independence assumption instead of autocorrelation for process monitoring is unsuitable. This study examines a generally weighted moving average (GWMA) with a time-varying control chart for monitoring the mean of a process based on autocorrelated observations from a first-order autoregressive process (AR(1)) with random error. Simulation is utilized to evaluate the average run length (ARL) of exponentially weighted moving average (EWMA) and GWMA control charts. Numerous comparisons of ARLs indicate that the GWMA control chart requires less time to detect various shifts at low levels of autocorrelation than those at high levels of autocorrelation. The GWMA control chart is more sensitive than the EWMA control chart for detecting small shifts in a process mean.     

Ewma control chart under linear drift

An accurate numerical procedure is presented for computing the average run length (ARL) of an exponentially weighted moving average (EWMA) chart under a linear drift in the process mean. The performance of an EWMA chart is then evaluated under a linear drift in the mean. In processes where gradual linear drifts rather than abrupt changes in the mean model the shifts in the mean more accurately, an evaluation of the performance of an EWMA chart under a linear drift is more appropriate. Tables of optimal smoothing parameters and control chart limits are given which make the design of EWMA charts easy.     

Combined Shewhart–EWMA control charts with estimated parameters

Shewhart and EWMA control charts can be suitably combined to obtain a simple monitoring scheme sensitive to both large and small shifts in the process mean. So far, the performance of the combined Shewhart–EWMA (CSEWMA) has been investigated under the assumption that the process parameters are known. However, parameters are often estimated from reference Phase I samples. Since chart performances may be even largely affected by estimation errors, we study the behaviour of the CSEWMA with estimated parameters in both in- and out-of-control situations. Comparisons with standard Shewhart and EWMA charts are presented. Recommendations are given for Phase I sample size requirements necessary to achieve desired in-control performance.     

汉代中央的厩

汉代中央的厩设置于长安城内外。东汉中央厩的数目较之西汉有所减省。中央厩由帝室财政系统掌管，其马匹主要从传统养马区选择，罚没、从地方征调也是中央厩马的重要来源。厩马主要供皇帝及帝室成员骑乘，祭祀、补充地方传置，以及作为军马等。中央厩所设置的职官主要有令、丞、监等，其秩级虽低，但和皇帝关系密切。厩在两汉时期的变化从一个侧面反映了汉代行政体系逐渐发育成熟。     

Parametric Inference and Dynamic State Recovery From Option Panels

We develop a new parametric estimation procedure for option panels observed with error. We exploit asymptotic approximations assuming an ever increasing set of option prices in the moneyness (cross‐sectional) dimension, but with a fixed time span. We develop consistent estimators for the parameters and the dynamic realization of the state vector governing the option price dynamics. The estimators converge stably to a mixed‐Gaussian law and we develop feasible estimators for the limiting variance. We also provide semiparametric tests for the option price dynamics based on the distance between the spot volatility extracted from the options and one constructed nonparametrically from high‐frequency data on the underlying asset. Furthermore, we develop new tests for the day‐by‐day model fit over specific regions of the volatility surface and for the stability of the risk‐neutral dynamics over time. A comprehensive Monte Carlo study indicates that the inference procedures work well in empirically realistic settings. In an empirical application to S&P 500 index options, guided by the new diagnostic tests, we extend existing asset pricing models by allowing for a flexible dynamic relation between volatility and priced jump tail risk. Importantly, we document that the priced jump tail risk typically responds in a more pronounced and persistent manner than volatility to large negative market shocks.     

Stable estimation of location parameter -nonasymptotic approach

Let X₁:, X₂:, …, X_n be iidrv's with cdf F?, F?(x)=F (x-θ), R. Let T be an equivariant median-unbiased estimator of θ. Let πε(F)={G = (1 -ε) F+εH, H any cdf} and let M(G, T) be a median of T if X₁ has cdf G. The oscillation of the bias of T, defined as

Bε(T)=sup (M(G₁ T) :G₁,G₂:∈π_σ:(F)} ,is considered and the estimator with the smallest B$epsi;(T) is explicitly constructed     

关于可拓集合零界的几个结论

本文给出了可拓集合的正域、负域及零界的若干结论     

由神恩到世俗:都铎时期英国济贫中区别对待的分析

都铎王朝是英国历史上一个发生急遽变动的重要时期。社会各方面的变动使英国济贫的特征发生了根本性的变化 :由神恩济贫走向世俗济贫。世俗济贫更多注重区别对待 ,对安定秩序的渴求和资本观念的增强是这一新特征形成的内在要求。本文从思想动机、政府立法和社会行为等三层面分析英国济贫中区别对待这一特征的形成和完善 ,从而指出区别性济贫是英国由传统社会向近代过渡的重要变革源泉     

离散非线性系统的有限时间控制

本文针对一类离散非线性系统的有限时间控制问题,利用线性矩阵不等式以及有限时间有界的概念,给出了离散非线性系统有限时间有界的充分性条件.     

Cyclically stable populations∗

The cyclically stable population relaxes the stable population assumption of fixed vital rates and replaces it with the assumption of a recurring sequence of schedules of vital rates. From any point (or stage) in one cycle of the sequence to the same stage in the next cycle, the cyclically stable population grows at a constant rate (λ). While the age composition of the cyclically stable population is different at different stages of the same cycle, it always has the same age composition at the same stage of every cycle. The essential dynamics of the cyclically stable model are captured by its birth projection matrix (BPM). The dominant eigenvalue of the BPM is growth rate A, and the right eigenvector associated with λ gives the within cycle‐birth sequence.

An important special case occurs when λ = 1, and a cyclically stationary population arises. Such populations challenge simplistic ideas about “Zero Population Growth.”; A population projection based on the sets of rates observed in the United States, 1970–90, shows a cyclically stationary population arising in less than 100 years. While it experiences no long term growth, that cyclically stationary population exhibits fluctuations in total size and considerable variability in age structure.