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.

相关问题

Error in undo(plot(a, aes(Nadir, mgam.lr1$yhat), se = T)) : could not find function "undo"

This error message indicates that the function "undo" is not recognized by R. It is possible that the function was not properly installed or loaded into the R environment. To resolve this issue, try installing or loading the package that contains the "undo" function. Alternatively, you may need to define or create the "undo" function yourself.

mgam<-gam(y~x+s(z),data=bc,family= poisson (),model=T)

This code uses the `gam` function in R to fit a generalized additive model (GAM) with a Poisson family to the data in `bc`, where `y` is the response variable, `x` is a predictor variable, and `z` is another predictor variable that is modeled using a smoothing function (`s(z)`). The `model=T` argument specifies that the model formula should be returned as part of the output, which can be useful for examining the model structure.