In pbs-assess/sdmTMB: Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB'

RW/AR(1) random field speed/Matrix sparseness

knitr::opts_chunk$set(
  echo = TRUE,
  message = FALSE,
  warning = FALSE,
  collapse = TRUE,
  comment = "#>",
  # prompt = FALSE,
  cache = TRUE,
  autodep = TRUE,
  results = 'hide'
  # fig.width = 7,
  # fig.asp = 0.618,
  # fig.pos = "ht",
  # cache.comments = TRUE,
  # dev = "pdf",
  # dpi = 140,
  # optipng = "-strip all"
  # R.options = list(prompt = "R> ", continue = "+ ")
)
knitr::knit_hooks$set(optipng = knitr::hook_optipng)
options(prompt = "R> ", continue = "+  ", width = 72, useFancyQuotes = FALSE)

# install_github("seananderson/sdmVAST")
# load_all("../sdmVAST")
library(sdmVAST)

dat <- sdmTMB::pcod
dat$X <- dat$X * 1000
dat$Y <- dat$Y * 1000
nd <- sdmTMB::qcs_grid
nd$X <- nd$X * 1000
nd$Y <- nd$Y * 1000

tictoc::tic()
fit_vast_rw <- sdmVAST(
  density ~ 1,
  data = dat,
  xy_cols = c("X", "Y"),
  zone = 9,
  n_knots = 200,
  time = "year",
  coord_type = "utm",
  spatial = "on",
  mean_per_time = "constant",
  spatiotemporal = "rw",
  newdata = nd,
  area_km = 4,
)
x <- tictoc::toc()
# fit_vast_rwfit
# fit_vast_rw$settings

x$callback_msg

tictoc::tic()
fit_vast_iid <- sdmVAST(
  density ~ 1,
  data = dat,
  xy_cols = c("X", "Y"),
  zone = 9,
  n_knots = 200,
  time = "year",
  coord_type = "utm",
  spatial = "on",
  mean_per_time = "constant",
  spatiotemporal = "iid",
  newdata = nd,
  area_km = 4,
)
x <- tictoc::toc()
# fit_vast_iid
# fit_vast_iid$settings

x$callback_msg

library(sdmTMB)
mesh <- sdmTMB::make_mesh(pcod, xy_cols = c("X", "Y"),
  mesh = fit_vast_iid$fit$spatial_list$MeshList$isotropic_mesh)
grid <- replicate_df(qcs_grid, "year", unique(pcod$year))

tictoc::tic()
fit_rw <- sdmTMB(
  density ~ 1,
  time = "year",
  data = pcod, mesh = mesh,
  spatiotemporal = "rw",
  silent = TRUE,
  family = delta_gamma(),
  do_index = TRUE,
  predict_args = list(newdata = grid),
  index_args = list(area = 4)

)
tictoc::toc()
# fit_rw

# in my local version, run the AR(1) with the SEPARABLE() formulation to check:
tictoc::tic()
fit_ar1 <- update(fit_rw, spatiotemporal = "ar1")
tictoc::toc()
# fit_ar1

tictoc::tic()
fit_iid <- update(fit_rw, spatiotemporal = "iid")
tictoc::toc()
# fit_iid

Matrix::image(fit_iid$tmb_obj$env$spHess(random = TRUE))
Matrix::image(fit_ar1$tmb_obj$env$spHess(random = TRUE))
Matrix::image(fit_rw$tmb_obj$env$spHess(random = TRUE))
Matrix::image(fit_vast_rw$fit$tmb_list$Obj$env$spHess(random = TRUE))