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简化单调回归方法AI 解读

Medical researchers often desire to categorize patients into monotonic response groups based on the relationship between continuous variables. Isotonic regression fits consist of level sets of increasing value, for which the estimated response is constant. However, the number of level sets obtained is often large, preventing simple description. This article introduces two new nonparametric methods called reduced isotonic regression and reduced monotonic regression, the…

简化单调回归方法AI 解读

Medical researchers often desire to categorize patients into monotonic response groups based on the relationship between continuous variables. Isotonic regression fits consist of level sets of increasing value, for which the estimated response is constant. However, the number of level sets obtained is often large, preventing simple description. This article introduces two new nonparametric methods called reduced isotonic regression and reduced monotonic regression, the…

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存在无应答时回归分析的样本量选择AI 解读

Assuming nonresponse, inference concerning the regression coefficients of a multiple linear regression is considered from a Bayesian viewpoint. We exploit a two-phase sampling scheme. At each phase the sample design is of the following type: Select a random sample of size n with n 1 responses obtained. Then, a subsample of size n 2(0 ≤ n 2 ≤ n — n 1) is selected from the n — n 1 nonrespondents. Assuming 100 percent response from the units in the subsample, the principal…

存在无应答时回归分析的样本量选择AI 解读

Assuming nonresponse, inference concerning the regression coefficients of a multiple linear regression is considered from a Bayesian viewpoint. We exploit a two-phase sampling scheme. At each phase the sample design is of the following type: Select a random sample of size n with n 1 responses obtained. Then, a subsample of size n 2(0 ≤ n 2 ≤ n — n 1) is selected from the n — n 1 nonrespondents. Assuming 100 percent response from the units in the subsample, the principal…

两个交叉乘积矩阵之和的逆矩阵的预后验分布AI 解读

In this note the preposterior distribution of the inverse of the sum S = S1 + S2 of two cross–product matrices is derived. It is assumed that the investigation consists of pilot and main random samples of multivariate normal random variables which yield the cross–product matrices S1 and S2, respectively. The desired preposterior distribution is that of S-1 conditional on S1. This result is useful in determining the optimal number of ‘nonrespondents’ it is appropriate to…

两个交叉乘积矩阵之和的逆矩阵的预后验分布AI 解读

In this note the preposterior distribution of the inverse of the sum S = S1 + S2 of two cross–product matrices is derived. It is assumed that the investigation consists of pilot and main random samples of multivariate normal random variables which yield the cross–product matrices S1 and S2, respectively. The desired preposterior distribution is that of S-1 conditional on S1. This result is useful in determining the optimal number of ‘nonrespondents’ it is appropriate to…