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Causal inference is a permanent challenge topic in statistics, data science, and many other applied fields. Existing machine learning methods often focus on the correlations in the data and ignore the...
Passengers left behind is an important measure to describe the degree of congestion in metro systems. Note that passengers' left behind probabilities are different for their different tap-in times. Th...
Sparsity is a naturally occurring characteristic in many real-world applications including signal denoising, outlier detection, and finance. On one hand, sparsity assumption allows people to tackle in...
In big data era, subsampling or sub-data selection techniques are often adopted to extract a fraction of informative individuals from the massive data. Existing subsampling algorithms focus mainly on ...
This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inf...
2018年2月,中国地质大学地球科学学院和生物地质与环境地质国家重点实验室何卫红教授团队,联合日本学者铃木纪毅博士,在国际地学领域著名期刊《Earth-Science Reviews》上在线发表题为“Low-latitudinal standard Permian radiolarian biostratigraphy for multiple purposes with Unitary Asso...
Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensi...
Modern scientific technology is providing a new class of simultaneous inference problems for the applied statistician, where there are hundreds or thousands or even more hypothesis tests to co...
In microarray studies, an important problem is to compare a predictor of disease outcome derived from gene expression levels to standard clinical predictors. Comparing them on the same dataset that ...
Bayesian Inference and the Parametric Bootstrap。
Modern statisticians are often presented with hundreds or thousands of hypothesis testing problems to evaluate at the same time, generated from new scientific technologies such as microarrays, ...
The use of multiscale statistics, that is, the simultaneous inference about various stretches of data via multiple localized statistics, is a natural and popular method for inference about, for exam...
Log-concave distributions are an attractive choice for modeling and inference, for several reasons: The class of log-concave distributions contains most of the commonly used parametric distributions ...
INFERENCE FOR NORMAL MIXTURE IN MEAN AND VARIANCE.

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