for(i in 1:500){tmp <- gam(a$结局~s(Nadir,k=3),family=binomial(link="logit"),data=a[sample(nrow(a),replace=T),]) out[,i]

<- tmp$coefficients}

This code runs a simulation of 500 iterations, where each iteration fits a generalized additive model (GAM) to a randomized subset of data from the variable "a". The GAM model includes a smooth term for the variable "Nadir" with a cubic spline function, and the response variable is the binary variable "结局". The family is set to binomial with a logit link function.

The output of each iteration is stored in a matrix called "out", with each column representing a different iteration and each row representing a coefficient from the fitted GAM model.

相关问题

Error: unexpected symbol in: "model <- gam(Y ~ s(X1)+s(X2)+s(X3)+s(X4)+s(X5), method = "REML", penalties = list(lm = 1) summary"

这个错误是因为在你的代码中，你在 `penalties` 参数中使用了 `list(lm = 1) summary` 这个表达式，而它是不合法的，应该将它分成两行写。你可以尝试将代码修改为如下形式：

model <- gam(Y ~ s(X1) + s(X2) + s(X3) + s(X4) + s(X5), method = "REML", 
             penalties = list(lm = 1))
summary(model)

这样应该就可以避免这个错误了。

mgam3<-gam(c$Mortality~ti(c$Age)+ti(c$Group)+ti(c$Age,c$Group),family = binomial(link = "logit"),data=c)

This code fits a generalized additive model (GAM) to the binary response variable "Mortality" using the predictor variables "Age" and "Group" as well as their interaction term. The "ti" function indicates that the predictor variables are included as smooth terms, allowing for non-linear relationships with the response variable. The "binomial" family and "logit" link function specify that the response variable follows a binomial distribution with a logit link function. The data used for the analysis is stored in the "c" data frame.