classical linear modelgeneralized linear modelsresiduals hypothesisTukey post hoc testThe classical linear model is based on the normal residuals hypothesis, which implies that the variable to be explained is also considered as being normally distributed, in other words, in a symmetrical manner. ...
设想一个分类或者回归问题,要预测一些随机变量y的值,作为x的一个函数。要导出适用于这个问题的广义线性模型 (Generalized Linear Model,缩写为 GLM),就要对我们的模型、给定x下y的条件分布来做出以下三个假设: y | x; \theta ∼ Exponential Family(\eta)——假设1 即给定x和\theta, y的分布属于指数分布族,...
diabetes_y_train)#Thecoefficientsprint('Coefficients: \n', regr.coef_)#Themean square errorprint("Residual sum of squares: %.2f"% np.mean((regr.predict(diabetes_X_test) - diabetes_y_test) ** 2))#Explained variance score: 1 is perfect prediction...
clustering, Newey–West, outer product of the gradient, bootstrap, and jackknife. The thorough coverage of model diagnostics includes measures of influence such as Cook’s distance, several forms of residuals, the Akaike and Bayesian information criteria, and variousR2-type measures of explained ...
Matching pursuit: locate a wavelet whose signature seems to correlate with the data collected; remove all traces of that signature from the data; and repeat until we have totally “explained” the data collected in terms of wavelet signatures. 就是先找出一个貌似是基的小波,然后去掉该小波在图像...
The thorough coverage of model diagnostics includes measures of influence such as Cook’s distance, several forms of residuals, the Akaike and Bayesian information criteria, and various R2-type measures of explained variability. After presenting general theory, Hardin and Hilbe then break down each ...
Model summary results and diagnostics are written to the messages window and charts will be created below the output feature class. The diagnostics and charts reported depend on theModel Typeparameter and are explained in detail in theHowGeneralized Linear Regressionworkstopic. ...
The relevance, or similarity, of each of the images to the given query is estimated by several generalized linear models, in particular local logistic regression models, explained in Section 3.2. It is also important that this relevance feedback procedure deals with diversity, so it is able to...
However, in making this adjustment, you lose the interpretation of the value as a proportion of the variance explained. In GWR, the effective number of degrees of freedom is a function of the neighborhood used, so the adjustment may be quite marked in comparison to a global model such as ...
For the regional county-level models, a modest amount of the variance in posterior estimates are explained by the predictor point estimate variances in the Midwest, Northeast, and South models. The Midwest analysis yields R2 > 17% for each linear model, and 24% of the variance in the ...