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应用统计属于统计学，统计学是一个独立的学科。理论统计侧重统计模型的建立，应用统计侧重各种方法在实际当中的应用。
TowerDebias: A Novel Unfairness Removal Method Based on the Tower Property
Arxiv
0+阅读 · 4月2日
Youthful perspectives on sustainability: Examining pro-environmental behaviors in tourism through latent class cluster analysis
Arxiv
0+阅读 · 4月3日
Joint Modeling of Spatial Dependencies Across Multiple Subjects in Multiplexed Tissue Imaging
Arxiv
0+阅读 · 4月3日
Beyond Discretization: A Continuous-Time Framework for Event Generation in Neuromorphic Pixels
Beyond Discretization: A Continuous-Time Framework for Event Generation in Neuromorphic Pixels
Arxiv
0+阅读 · 4月3日
Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting
Arxiv
0+阅读 · 4月3日
Stable EEG Source Estimation for Standardized Kalman Filter using Change Rate Tracking
Arxiv
0+阅读 · 3月29日
Hypergraph Representations of scRNA-seq Data for Improved Clustering with Random Walks
Arxiv
0+阅读 · 4月2日
Combining BART and Principal Stratification to estimate the effect of intermediate variables on primary outcomes with application to estimating the effect of family planning on employment in Nigeria and Senegal
Combining BART and Principal Stratification to estimate the effect of intermediate variables on primary outcomes with application to estimating the effect of family planning on employment in Nigeria and Senegal
Arxiv
0+阅读 · 4月3日
Predicting passenger injury distributions under uncertainty variables using Gaussian process modeling with GHBMC
Arxiv
0+阅读 · 4月3日
The "Days of Learning" Metric for Education Evaluations
Arxiv
0+阅读 · 4月3日
Reducing Differential Item Functioning via Process Data
Arxiv
0+阅读 · 3月31日
Granger causal inference for climate change attribution
Arxiv
0+阅读 · 4月2日
Quantile Treatment Effects in High Dimensional Panel Data
Arxiv
0+阅读 · 4月1日
pumBayes: Bayesian Estimation of Probit Unfolding Models for Binary Preference Data in R
Arxiv
0+阅读 · 4月1日
Addressing an extreme positivity violation to distinguish the causal effects of surgery and anesthesia via separable effects
Arxiv
0+阅读 · 4月1日
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