glm

问题 I am trying to get the F-statistic and p-value for each of the covariates in GLM. In Python I am using the stats mode.formula.api to conduct the GLM. formula = 'PropNo_Pred ~ Geography + log10BMI + Cat_OpCavity + CatLes_neles + CatRural_urban + \ CatPred_Control + CatNative_Intro + Midpoint_of_study' mod1 = smf.glm(formula=formula, data=A2, family=sm.families.Binomial()).fit() mod1.summary() After that I am trying to do the ANOVA test for this model using the anova in statsmodels.stats table1

问题 I am trying to get the F-statistic and p-value for each of the covariates in GLM. In Python I am using the stats mode.formula.api to conduct the GLM. formula = 'PropNo_Pred ~ Geography + log10BMI + Cat_OpCavity + CatLes_neles + CatRural_urban + \ CatPred_Control + CatNative_Intro + Midpoint_of_study' mod1 = smf.glm(formula=formula, data=A2, family=sm.families.Binomial()).fit() mod1.summary() After that I am trying to do the ANOVA test for this model using the anova in statsmodels.stats table1

问题 Issue I am attempting to undertake an analysis using the Tidymodels Package in R . I am following this tutorial below regarding decision tree learning in R:- Tutorial https://bcullen.rbind.io/post/2020-06-02-tidymodels-decision-tree-learning-in-r/ I have a data frame called FID (see below) where the dependent variable is the frequency (numeric) , and the predictor variables are:- Year (numeric), Month (factor), Monsoon (factor), and Days (numeric). I believe I have successfully followed the

来源： https://stackoverflow.com/questions/37917437/loglik-lm-why-does-r-use-p-1-instead-of-p-for-degree-of-freedom

来源： https://stackoverflow.com/questions/37917437/loglik-lm-why-does-r-use-p-1-instead-of-p-for-degree-of-freedom

来源： https://stackoverflow.com/questions/37917437/loglik-lm-why-does-r-use-p-1-instead-of-p-for-degree-of-freedom

来源： https://stackoverflow.com/questions/18475681/using-the-predict-function-with-glm

来源： https://stackoverflow.com/questions/18475681/using-the-predict-function-with-glm

来源： https://stackoverflow.com/questions/50764044/visualizing-marginal-effect-of-two-way-interaction-of-binary-logistic-model-in-g

问题 I have: x = rnorm(100) # Partie b z = rbinom(100,1,0.60) # Partie c y = 1.4 + 0.7*x - 0.5*z # Partie d x1 = abs(x) y1 = abs(y) Don<-cbind(y1,x1,z) Don1 <- data.frame(Don) Reg <- glm(y1~x1+z,family=poisson(link="log"),Don1) # Partie e #Biais de beta Reg.cf <- coef(Reg) biais0 = Reg.cf[1] - 1.4 biais1 = Reg.cf[2] - 0.7 biais2 = Reg.cf[3] + 0.5 And I need to repeat all this 100 times in order to have different coefficient and calculate the bias and then put the mean of each biais in a text file.