0
$\begingroup$

I have an issue implementing poly function in R. Following are my variables.

X.des.e = three continuous variables

X.des.detection = two continuous variables

model = glm(Pres ~ poly(X.data,degree = 2, raw = TRUE ) + (X.data2), family = poisson(), weights = p.wt)

To get predictions I use

X.data=cbind(X.data,X.data2)

predictions = predict(model, newdata=X.data, response=TRUE)

However, if the values of X.data set to its minimal (or to any other value)and do predictions to this new dataset, but original predictions won't change. Any suggestion?

New contributor
Bandara is a new contributor to this site. Take care in asking for clarification, commenting, and answering. Check out our Code of Conduct.
$\endgroup$

closed as off-topic by whuber Feb 10 at 13:22

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "This question appears to be off-topic because EITHER it is not about statistics, machine learning, data analysis, data mining, or data visualization, OR it focuses on programming, debugging, or performing routine operations within a statistical computing platform. If the latter, you could try the support links we maintain." – whuber
If this question can be reworded to fit the rules in the help center, please edit the question.

  • $\begingroup$ Correction: To get predictions I use X.data3=cbind(X.data,X.data2) However, if the values of X.data2 set to its minimal (or to any other value)and do predictions to this new dataset, but original predictions won't change. Any suggestion? $\endgroup$ – Bandara Feb 10 at 12:01