After adjusting for ascertainment, they found maximum likelihood estimates of the measured exposure effects. Although it is appealing that this model accounts for genetic correlations as well as for the ascertainment of families, in order to perform an analysis one needs to specify the distribution ...
aHowever, there is not a universal robustness and, especially if the hyperparameter is estimated, it could be important to assess the actual sensitivity of the inference to the specification of the hyperparameter. 然而,没有普遍强壮,并且,特别是如果hyperparameter估计,估计推断的实际敏感性到hyperparamet...
Robustness of nonlinearity and chaos tests to measurement error, inference methods, and sample size. Discusses the robustness of nonlinearity and chaos tests to measurement error, inference methods, and sample size. Empirical difficulties of the tests; Tests for nonlinearity or chaos to various monetary...
That economists know next to nothing about measurement errors is not a good reason to assume them away. A more meaningful approach might be to investigate under which classes of measurement errors a given null hypothesis is rejected or not rejected. This paper illustrates this approach for the ...
CODE_OF_CONDUCT.md CONTRIBUTING.md Dockerfile LICENSE MAINTAINERS.md MANIFEST.in Makefile PULL_REQUEST_TEMPLATE.md README-cn.md README.md SECURITY.md codecov.yml conftest.py pyproject.toml readthedocs.yml requirements_test.txt run_tests.sh ...
Deep learning-based image analysis offers great potential in clinical practice. However, it faces mainly two challenges: scarcity of large-scale annotated clinical data for training and susceptibility to adversarial data in inference. As an example, an artificial intelligence (AI) system could check ...
(Efron & Tibshirani, 1994) have been proposed as approaches to evaluate uncertainty in social network analysis (Lusseau et al., 2008, Whitehead, 2008b) A bootstrapping procedure involves randomly resampling the data stream (i.e. the observation of groups across time) with replacement such that...
RENOIR supports three types of methods to randomly split the input data into independent training and evaluation sets: sampling without replacement, sampling with replacement (bootstrap), and k-fold cross-validation. If a stratification variable is provided, a stratified approach is adopted, where the...
replacement_checkpoint_path, replacement_tokenizer_path: path of the model checkpoint used to generate word replacement candidates num_replacement_retry: Some word replacements generated by the replacement_model can be invalid and filtered out. Therefore, we can set anum_replacement_retryto retry the ...
Single-cell messenger RNA sequencing (scRNA-seq) has emerged as a powerful tool to study cellular heterogeneity within complex tissues. Subpopulations of cells with common gene expression profiles can be identified by applying unsupervised clustering alg