Fix extra_time/newdata/offset issue #270

R/predict.R

@@ -379,6 +379,7 @@ predict.sdmTMB <- function(object, newdata = NULL,
       newdata[["_sdmTMB_fake_nd_"]] <- FALSE
       fake_nd[["_sdmTMB_fake_nd_"]] <- TRUE
       newdata <- rbind(newdata, fake_nd)
+      if (!is.null(offset)) offset <- c(offset, rep(0, nrow(fake_nd))) # issue 270
     }
 
     # If making population predictions (with standard errors), we don't need
@@ -828,6 +829,7 @@ predict.sdmTMB <- function(object, newdata = NULL,
     #   nd[[paste0("zeta_s_", object$spatial_varying[z])]] <- r$zeta_s_A[,z,1]
     # }
     nd$epsilon_st <- r$epsilon_st_A_vec[,1]# DELTA FIXME
+    nd <- nd[!nd[[object$time]] %in% object$extra_time, , drop = FALSE] # issue 270
     obj <- object
   }
 

tests/testthat/test-extra-time.R

@@ -0,0 +1,27 @@
+test_that("extra time, newdata, and offsets work", {
+  # https://github.com/pbs-assess/sdmTMB/issues/270
+  skip_on_cran()
+  skip_on_ci()
+  pcod$os <- rep(log(0.01), nrow(pcod)) # offset
+  m <- sdmTMB(
+    data = pcod,
+    formula = density ~ 0,
+    time_varying = ~ 1,
+    offset = pcod$os,
+    family = tweedie(link = "log"),
+    spatial = "off",
+    time = "year",
+    extra_time = c(2006, 2008, 2010, 2012, 2014, 2016),
+    spatiotemporal = "off"
+  )
+  p1 <- predict(m, offset = pcod$os)
+  p2 <- predict(m, newdata = pcod, offset = pcod$os)
+  p3 <- predict(m, newdata = pcod)
+  p4 <- predict(m, newdata = pcod, offset = rep(0, nrow(pcod)))
+  expect_equal(nrow(p1), nrow(pcod))
+  expect_equal(nrow(p2), nrow(pcod))
+  expect_equal(nrow(p3), nrow(pcod))
+  expect_equal(nrow(p4), nrow(pcod))
+  expect_equal(p1$est, p2$est)
+  expect_equal(p3$est, p4$est)
+})