I am trying to do spatial predictions with GAM and rasters. I have a raster file of depth data (Depth_R.asc), and presence and absence data of species from 248 locations (Depth.csv) . First I fitted these 248 data and then used raster:predict function to predict the occurrence probability of species over my whole study area depth data (Depth_R.asc). But when I want to do that I get following errors: Error in p[-naind, ] <- predv : number of items to replace is not a multiple of replacement length In addition: Warning messages: 1: In predict.gam(model, blockvals, ...) : not all required variables have been supplied in newdata!
All data are available at:https://drive.google.com/drive/folders/15uRsWqgG0tcOlfuU9WSF-vTG6gJkuhLd?usp=sharing
My code is:
library(raster)
library(mgcv)
Data = read.csv("Depth.csv")
model <- gam(PA ~s(Depth), method="REML",family = binomial("logit"), data=Data)
X = raster("Depth_R.asc", level = 1)
p <- raster::predict(X, model, type="response")
How to solve this problem?