Robust model selectionIn recent years, in the literature of linear regression models, robust model selection methods have received increasing attention when the datasets contain even a small fraction of outliers
(2005): Outlier robust model selection in linear regression. Journal of the American Statistical Association 100 ( 472 ), 1297-1310 .Muller S, Welsh AH (2005). "Outlier Robust Model Selection in Linear Regression." Journal of the American Statistical Association, 100(472), 1297-1310. doi:...
robustfitis useful when you simply need the output arguments of the function or when you want to repeat fitting a model multiple times in a loop. If you need to investigate a robust fitted regression model further, create a linear regression model objectLinearModelby usingfitlm. Set the value...
SVD与主成分的关系:特征值越大,方差越大。 三、Robust regression鲁棒线性回归(Laplace/Student似然+均匀先验) 因为先验服从均匀分布,所以求鲁棒线性回归即求Laplace/Student最大似然。在heavy tail(奇异点较多)情况下用鲁棒线性回归,因为Laplace/Student分布比高斯分布更鲁棒。 似然函数为: 由于零点不可微,所以求解析解...
The idea of generalized linear models (GLM) generated by Nelder and Wedderburn ( 1972 ) seeks to extend the domain of applicability of the linear model by relaxing the normality assumption. In particular, GLM can be used to model the relationship between the explanatory variable, X , and a ...
Linear Regression Model Selection Based on Robust Bootstrapping Technique. American Journal of Applied Sciences 6 (6), 1191-1198Uraibi HS, Midi H, Talib BA, Yousif JB (2009) Linear regression model selection based on robust bootstrapping technique. Am J Appl Sci 6:1191–1198. doi: 10....
Morgenthaler, S., R. E. Welsch, and A. Zenide, 2003. Algorithms for Robust Model Selection in Linear Regression, in Theory and Applications of Recent Robust Methods, eds. M Hubert, G. Pison, A. Struyf, and S. Van Aelst, Basel, Switzerland: Birkhauser-Verlag, 195-206....
partial linearThe proper combination of parametric and nonparametric regression procedures can improve upon the shortcomings of each when used individually. Considered is the situation where the researcher has an idea of which parametric model should explain the behavior of the data, but this model is...
• Least Square Linear Model • Robust Methods • Resistant Methods Least Square Linear Model • Is the traditional Linear Model Regression • Determines the best fitting line as the line that minimizes Sum of Square of Errors. SSE=Σ(Y i - Y i -hat) • If all the assumptions...
所以这里的问题就变成了是否存在这样一个Efficient Influence Function使得所有的parametric submodel的 \mathcal{P}_t(\phi(O,\mathcal{P}_t))=0 ?好吧,既然是假设,那么我们就假设存在了,如果我们很幸运推导出来某种形式满足这个条件,我们是不是可以用这个公式当做Efficient Influence Function来使用?所以这里我们...