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In recent years, statistical process control (SPC)
has been widely used to monitor the performance of clinical practitioners,
such as surgeons and general practitioners. In this paper, two risk-adjusted
geometric control charts namely cumulative sum (CUSUM) and weighted likelihood
ratio test (WLRT) are proposed to monitor surgery performance in phase II.
The performance of the proposed control charts is evaluated and compared by
simulation experiments for different shift values in the parameters of a
risk-adjusted logistic regression model in terms of the average run length
(ARL) criterion. The results show that all methods work well in the sense
that they can effectively detect shifts in the process parameters.
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In this paper, we introduce a concept of Poisson $p$-mean almost automorphy for stochastic processes and give the composition theorems for (Poisson) $p$-mean almost automorphic functions under non-Lipschitz conditions. Our abstract results are, subsequently, applied to study a class of neutral stochastic evolution equations driven by L\'evy noise, and we present sufficient conditions for the existence of square-mean almost automorphic mild solutions. An example is provided to illustrate the effectiveness of the proposed result.
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In this article, applying the result of complete convergence for negatively associated (NA) random variables which is obtained by Chen et al.\ucite{14}, the equivalent conditions of complete convergence for weighted sums of arrays of row-wise negatively associated random variables is investigated. As a result, the corresponding results of Liang\ucite{11} is generalized, moreover, the proof procedure is simplified greatly which is different from truncation method of Liang's. Thus, Gut's\ucite{13} result on Ces\`{a}ro summation of i.i.d. random variables is extended.
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We extend the instrumental variable method for the mean regression models to linear quantile regression models with errors-in-variables. The proposed estimator is consistent and asymptotically normally distributed under some fairly general conditions. Moreover, this approach is practical and easy to implement. Simulation studies show that the finite sample performance of the estimator is satisfactory. The method is applied to a real data study of education and wages.
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For linear quantile regression model, this paper proves that the test statistics, besed on smoothed empirical likelihood (SEL) method and least absolute deviation (LAD) method, both converge weakly to a noncentral Chi-square distribution under the local alternatives $H_1:\beta=\beta_0+a_n$, where $\beta$ is the true parameter. Simulation results show that the SEL method is more efficient than the LAD method.
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In this paper, the empirical Bayes (EB) two-sided test for parameter of Cox models is investigated under square loss functions. At first by using recursive kernel estimation of probability function the empirical Bayes two-sided test rule is constructed. It proves that the proposed empirical Bayes test rule is asymptotic optimal and convergence rates are obtained under suitable conditions. Finally an example of satisfying theorem conditions is given.
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Clustered interval-censored failure time data often arises in medical studies when study subjects come from the same cluster. Furthermore, the failure time may be related to the cluster size. A simple and common approach is to simplify interval-censored data due to the lack of proper inference procedures for direct analysis. For this reason, we proposed the within-cluster resampling-based method to consider the case II interval-censored data under the additive hazards
model. With-cluster resampling is simple but computationally intensive. A major advantage of the proposed approach is that the estimator can be easily implemented when the cluster size is informative. Asymptotic properties and some simulation results are provided and indicate that the proposed approach works well.
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In this paper an efficient estimation methodology for the partially linear models with random effects is proposed. For this, we use the generalized least square estimate (GLSE) and the B-splines methods to estimate the unknowns, and employ the penalized least square method to obtain the estimators of the random effects item. Further, we also consider the estimation for the variance components. Compared with the existing methods, our proposed methodology performs well. The asymptotic properties of the estimators are obtained. A simulation study is carried out to assess the performance of our proposed methodology.
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This is the fourth article on the same topic.The earlier ones are[1],[2],[5]. Here,a brief introduction to a number of landmark events in a decade, which indicates that the probability theory has been moving to mature, becomes a normal branch of mathematics. We introduce this relatively young mathematics disciplines of the growth bit. And then combined with personal experience, focusing on the cross-penetration and typical results of probability theory with statistical physics and other disciplines branch of mathematics in the past decade. This article is not subject review, but only hope that through one or two sides, showing the development and progress of probability theory.
