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划定入选名单：大规模推断中的排序与筛选改进AI 解读

Summary Identifying leading measurement units from a large collection is a common inference task in various domains of large-scale inference. Testing approaches, which measure evidence against a null hypothesis rather than effect magnitude, tend to overpopulate lists of leading units with those associated with low measurement error. By contrast, local maximum likelihood approaches tend to favour units with high measurement error. Available Bayesian and empirical Bayesian…

部分可交换二元数据的依赖阶数评估AI 解读

The problem we consider is how to assess the order of serial dependence within partially exchangeable binary sequences. We obtain exact conditional tests comparing any two orders by finding the conditional distribution of data given certain transition counts. These tests are facilitated with a new Monte Carlo scheme. Asymptotic tests are also discussed. In particular, we show that the likelihood ratio tests have an asymptotic chi-squared distribution, thus generalizing the…

半参数二元回归的贝叶斯推断AI 解读

We propose a regression model for binary response data that places no structural restrictions on the link function except monotonicity and known location and scale. Predictors enter linearly. We demonstrate Bayesian inference calculations in this model. By modifying the Dirichlet process, we obtain a natural prior measure over this semiparametric model, and we use Polya sequence theory to formulate this measure in terms of a finite number of unobserved variables. We design a…

早期造血过程的随机建模AI 解读

Hematopoiesis is the body's way of making the cellular constituents of blood. Oxygen transport, response to infections, and control of bleeding are among the functions of different mature blood cells. These specific functions are acquired as cells mature in the bone marrow. Stem cells are the “master cells” at the top of this pedigree, having within them the capacity to reconstitute the entire system. Although the latter stages of hematopoiesis are fairly well understood,…

早期造血过程的随机建模AI 解读

Hematopoiesis is the body's way of making the cellular constituents of blood. Oxygen transport, response to infections, and control of bleeding are among the functions of different mature blood cells. These specific functions are acquired as cells mature in the bone marrow. Stem cells are the “master cells” at the top of this pedigree, having within them the capacity to reconstitute the entire system. Although the latter stages of hematopoiesis are fairly well understood,…

Bootstrap 样本循环利用：嵌套 Bootstrap 的蒙特卡洛替代方案AI 解读

A Monte Carlo algorithm is described that can be used in place of the nested bootstrap. It is particularly advantageous when there is a premium on the number of bootstrap samples, either because samples are hard to generate or because expensive computations are applied to each sample. This recycling algorithm is useful because it enables inference procedures like prepivoting and bootstrap iteration in models where nested bootstrapping is computationally impractical.…

Bootstrap 循环利用：嵌套 Bootstrap 的蒙特卡洛替代方案AI 解读

A Monte Carlo algorithm is described that can be used in place of the nested bootstrap. It is particularly advantageous when there is a premium on the number of bootstrap samples, either because samples are hard to generate or because expensive computations are applied to each sample. This recycling algorithm is useful because it enables inference procedures like prepivoting and bootstrap iteration in models where nested bootstrapping is computationally impractical.…

使用加权似然 Bootstrap 的近似贝叶斯推断AI 解读

SUMMARY We introduce the weighted likelihood bootstrap (WLB) as a way to simulate approximately from a posterior distribution. This method is often easy to implement, requiring only an algorithm for calculating the maximum likelihood estimator, such as iteratively reweighted least squares. In the generic weighting scheme, the WLB is first order correct under quite general conditions. Inaccuracies can be removed by using the WLB as a source of samples in the…

用秩统计理论研究一般 Bootstrap 的一致性AI 解读

A general notion of a bootstrapped mean constructed by exchangeably weighting sample points is introduced. Consistency of this generalized bootstrapped mean, which includes proposals of Efron and Rubin among others, is proved by classical linear rank statistics theory. The consistency of generalized bootstrapped empirical and quantile processes is also established.