四元数海森堡群上关于Full拉普拉斯算子的波动方程的Strichartz估计，宋乃琪，赵纪满，在本文中,我们通过讨论和四元数海森堡群上与Full拉普拉斯算子相关的Littlewood-Paley分解及齐型Besov空间的性质,得到了相关于Full拉普拉斯�

回归参数估计 使用不同方法的回归模型中参数估计的R代码： 最小二乘 梯度下降 大都会-哈丁斯 使用JAGS进行吉布斯采样 该代码用于具有一个预测变量的线性回归问题（单变量回归）。 目的是通过一个简单的示例并为所有方法提供基本实现，以介绍机器学习中广泛使用的重要方面，例如梯度下降和蒙特卡洛方法。 此博客文章中介绍了不同的方法和代码： :

结合随机森林和LSBoost进行证券市场指数预测。 Abstract— This research work emphases on the prediction of future stock market index values based on historical data. The experimental evaluation is based on historical data of 10 years of two indices, namely, CNX Nifty and S&P Bombay Stock Exchange (BSE) Sensex from Indian stock markets. The predictions are made for 1–10, 15, 30, and 40 days in advance. This work proposes to combine the predictions/estimates of the ensemble of trees in a Random Forest using LSboost (i.e. LS-RF). The prediction performance of the proposed model is compared with that of well-known Support Vector Regression. Technical indicators are selected as inputs to each of the prediction models. The closing value of the stock price is the predicted variable. Results show that the proposed scheme outperforms Support Vector Regression and can be applied successfully for building predictive models for stock prices prediction.

PETER J. HUBER 的一篇论文，对于理解最大似然估计很有帮助，讨论了非标准情形下最大似然估计的表现。

US_Provisional Life Expectancy Estimates for 2020

logistic regression on the SVM’s scores, fit by an additional cross-validation on the training data. In the multiclass case, this is extended as per

Instabilities of Regression Estimates Relating Air Pollution to Mortality

德州基本的数学描述