This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo-score is constr...This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo-score is constructed to estimate the regression parameters.The resulting estimator is shown to be consistent and asymptotically normally distributed.The limiting variance-covariance matrix can be consistently estimated by the nested case-control data.A simulation study is conducted to assess the finite sample performance of the proposed estimator and a real example is provided for illustration.展开更多
Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs ...Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs are also obtained.展开更多
Sequential Latin hypercube designs(SLHDs) have recently received great attention for computer experiments, with much of the research restricted to invariant spaces. The related systematic construction methods are infl...Sequential Latin hypercube designs(SLHDs) have recently received great attention for computer experiments, with much of the research restricted to invariant spaces. The related systematic construction methods are inflexible, and algorithmic methods are ineffective for large designs. For designs in contracting spaces, systematic construction methods have not been investigated yet. This paper proposes a new method for constructing SLHDs via good lattice point sets in various experimental spaces. These designs are called sequential good lattice point(SGLP) sets. Moreover, we provide efficient approaches for identifying the(nearly)optimal SGLP sets under a given criterion. Combining the linear level permutation technique, we obtain a class of asymptotically optimal SLHDs in invariant spaces, where the L1-distance in each stage is either optimal or asymptotically optimal. Numerical results demonstrate that the SGLP set has a better space-filling property than the existing SLHDs in invariant spaces. It is also shown that SGLP sets have less computational complexity and more adaptability.展开更多
基金Supported by the National Natural Science Foundation of China(10971033,11101091)
文摘This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo-score is constructed to estimate the regression parameters.The resulting estimator is shown to be consistent and asymptotically normally distributed.The limiting variance-covariance matrix can be consistently estimated by the nested case-control data.A simulation study is conducted to assess the finite sample performance of the proposed estimator and a real example is provided for illustration.
文摘Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs are also obtained.
基金supported by National Natural Science Foundation of China(Grant Nos.11871288,12131001,and 12226343)National Ten Thousand Talents Program+2 种基金Fundamental Research Funds for the Central UniversitiesChina Scholarship CouncilU.S.National Science Foundation(Grant No.DMS18102925)。
文摘Sequential Latin hypercube designs(SLHDs) have recently received great attention for computer experiments, with much of the research restricted to invariant spaces. The related systematic construction methods are inflexible, and algorithmic methods are ineffective for large designs. For designs in contracting spaces, systematic construction methods have not been investigated yet. This paper proposes a new method for constructing SLHDs via good lattice point sets in various experimental spaces. These designs are called sequential good lattice point(SGLP) sets. Moreover, we provide efficient approaches for identifying the(nearly)optimal SGLP sets under a given criterion. Combining the linear level permutation technique, we obtain a class of asymptotically optimal SLHDs in invariant spaces, where the L1-distance in each stage is either optimal or asymptotically optimal. Numerical results demonstrate that the SGLP set has a better space-filling property than the existing SLHDs in invariant spaces. It is also shown that SGLP sets have less computational complexity and more adaptability.
