MakeInput_Fn: This function generates the stochastic partial differential...
In James-Thorson/spatial_factor_analysis: Package for implementing spatial factor analysis (SFA), a spatial analogue of conventional factor analysis
Usage
1
MakeInput_Fn(Version, Y, X, Y_Report = NULL, LastRun = NULL, Loc, isPred, ErrorDist, ObsModel, VaryingKappa, n_factors, n_stations, Use_REML, Aniso)
Arguments
Version
Y
X
Y_Report
LastRun
Loc
isPred
ErrorDist
ObsModel
VaryingKappa
n_factors
n_stations
Use_REML
Aniso
mesh
spde
Examples
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##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (Version, Y, X, Y_Report = NULL, LastRun = NULL, Loc,
isPred, ErrorDist, ObsModel, VaryingKappa, n_factors, n_stations,
Use_REML, Aniso)
{
mesh = inla.mesh.create(Loc[, c("x", "y")], plot.delay = NULL,
refine = FALSE)
spde = inla.spde2.matern(mesh, alpha = 2)
Dset = 1:2
TV = mesh$graph$tv
V0 = mesh$loc[TV[, 1], Dset]
V1 = mesh$loc[TV[, 2], Dset]
V2 = mesh$loc[TV[, 3], Dset]
E0 = V2 - V1
E1 = V0 - V2
E2 = V1 - V0
TmpFn = function(Vec1, Vec2) abs(det(rbind(Vec1, Vec2)))
Tri_Area = rep(NA, nrow(E0))
for (i in 1:length(Tri_Area)) Tri_Area[i] = TmpFn(E0[i, ],
E1[i, ])/2
NAind = ifelse(is.na(Y), 1, 0)
if (is.null(Y_Report))
Y_Report = array(0, dim = dim(Y))
n_species = ncol(Y)
n_fit = nrow(Y)
if (Version == "spatial_factor_analysis_v18")
Data = list(Y = Y_fit, Y_Report = Y_Report, NAind = NAind_fit,
isPred = isPred, ErrorDist = as.integer(2), VaryingKappa = as.integer(VaryingKappa),
n_species = n_species, n_stations = n_fit, n_factors = n_factors,
meshidxloc = mesh$idx$loc - 1, n_p = ncol(X_fit),
X = X_fit, G0 = spde$param.inla$M0, G1 = spde$param.inla$M1,
G2 = spde$param.inla$M2)
if (Version %in% c("spatial_factor_analysis_v19", "spatial_factor_analysis_v20"))
Data = list(Pen_Vec = c(0, 0), Y = Y_fit, Y_Report = Y_Report,
NAind = NAind_fit, isPred = isPred, ErrorDist = as.integer(2),
VaryingKappa = as.integer(VaryingKappa), n_species = n_species,
n_stations = n_fit, n_factors = n_factors, meshidxloc = mesh$idx$loc -
1, n_p = ncol(X_fit), X = X_fit, G0 = spde$param.inla$M0,
G1 = spde$param.inla$M1, G2 = spde$param.inla$M2)
if (Version %in% c("spatial_factor_analysis_v21", "spatial_factor_analysis_v22"))
Data = list(Aniso = as.integer(Aniso), Pen_Vec = c(0,
0), Y = Y_fit, Y_Report = Y_Report, NAind = NAind_fit,
isPred = isPred, ErrorDist = as.integer(2), VaryingKappa = as.integer(VaryingKappa),
n_species = n_species, n_stations = n_fit, n_factors = n_factors,
n_i = mesh$n, meshidxloc = mesh$idx$loc - 1, n_p = ncol(X_fit),
X = X_fit, n_tri = nrow(mesh$graph$tv), Tri_Area = Tri_Area,
E0 = E0, E1 = E1, E2 = E2, TV = TV - 1, G0 = spde$param.inla$M0,
G0_inv = as(diag(1/diag(spde$param.inla$M0)), "dgTMatrix"),
G1 = spde$param.inla$M1, G2 = spde$param.inla$M2)
if (StartValue == "Default" | is.null(LastRun)) {
if (Version %in% c("spatial_factor_analysis_v18", "spatial_factor_analysis_v19"))
Params = list(beta = matrix(0, nrow = ncol(X), ncol = n_species,
byrow = TRUE), Psi_val = rep(1, n_factors * n_species -
n_factors * (n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl = matrix(-2,
nrow = 3, ncol = n_species), Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v20")
Params = list(beta = matrix(0, nrow = ncol(X), ncol = n_species,
byrow = TRUE), Psi_val = rep(1, n_factors * n_species -
n_factors * (n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl_NB1 = NA,
ln_VarInfl_NB2 = NA, ln_VarInfl_ZI = NA, Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v21")
Params = list(ln_H_input = c(0, -10, 0), beta = matrix(0,
nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = rep(1, n_factors * n_species - n_factors *
(n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl_NB1 = NA,
ln_VarInfl_NB2 = NA, ln_VarInfl_ZI = NA, Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v22")
Params = list(ln_H_input = c(0, 0), beta = matrix(0,
nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = rep(1, n_factors * n_species - n_factors *
(n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl_NB1 = NA,
ln_VarInfl_NB2 = NA, ln_VarInfl_ZI = NA, Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (ObsModel == "Poisson") {
Params[["ln_VarInfl_NB1"]] = rep(-20, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin1") {
Params[["ln_VarInfl_NB1"]] = rep(-2, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin12") {
Params[["ln_VarInfl_NB1"]] = rep(-2, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-2, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
}
if (StartValue == "Last_Run" & !is.null(LastRun)) {
Par_last = LastRun$opt$par
Par_best = LastRun$obj$env$last.par.best
if (Version %in% c("spatial_factor_analysis_v18", "spatial_factor_analysis_v19"))
Params = list(beta = matrix(Par_last[which(names(Par_last) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl = Par_last[which(names(Par_last) ==
"ln_VarInfl")], Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v20")
Params = list(beta = matrix(Par_last[which(names(Par_last) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl_NB1 = NA, ln_VarInfl_NB2 = NA,
ln_VarInfl_ZI = NA, Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v21")
Params = list(ln_H_input = Par_last[which(names(Par_last) ==
"ln_H_input")], beta = matrix(Par_last[which(names(Par_last) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl_NB1 = NA, ln_VarInfl_NB2 = NA,
ln_VarInfl_ZI = NA, Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v22")
Params = list(ln_H_input = Par_best[which(names(Par_best) ==
"ln_H_input")], beta = matrix(Par_best[which(names(Par_best) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl_NB1 = NA, ln_VarInfl_NB2 = NA,
ln_VarInfl_ZI = NA, Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (ObsModel == "Poisson") {
Params[["ln_VarInfl_NB1"]] = rep(-20, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin1") {
Params[["ln_VarInfl_NB1"]] = Par_best[which(names(Par_best) ==
"ln_VarInfl_NB1")]
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin12") {
Params[["ln_VarInfl_NB1"]] = Par_best[which(names(Par_best) ==
"ln_VarInfl_NB1")]
Params[["ln_VarInfl_NB2"]] = Par_best[which(names(Par_best) ==
"ln_VarInfl_NB2")]
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (Version %in% c("spatial_factor_analysis_v20", "spatial_factor_analysis_v21")) {
if (Aniso == 0)
Params[["ln_H_input"]] = c(0, -10, 0)
}
if (Version %in% c("spatial_factor_analysis_v22")) {
if (Aniso == 0)
Params[["ln_H_input"]] = c(0, 0)
}
}
Map = list()
if (ObsModel == "Poisson") {
Map[["ln_VarInfl_NB1"]] = factor(rep(NA, n_species))
Map[["ln_VarInfl_NB2"]] = factor(rep(NA, n_species))
Map[["ln_VarInfl_ZI"]] = factor(rep(NA, n_species))
}
if (ObsModel == "NegBin1") {
Map[["ln_VarInfl_ZI"]] = factor(rep(NA, n_species))
Map[["ln_VarInfl_NB2"]] = factor(rep(NA, n_species))
}
if (ObsModel == "NegBin12") {
Map[["ln_VarInfl_ZI"]] = factor(rep(NA, n_species))
}
if (Version %in% c("spatial_factor_analysis_v18", "spatial_factor_analysis_v19",
"spatial_factor_analysis_v20", "spatial_factor_analysis_v21")) {
if (Aniso == 0)
Map[["ln_H_input"]] = factor(rep(NA, 3))
if (Aniso == 1 & VaryingKappa == 0)
Map[["log_kappa_input"]] = factor(NA)
}
if (Version %in% c("spatial_factor_analysis_v22")) {
if (Aniso == 0)
Map[["ln_H_input"]] = factor(rep(NA, 2))
}
Random = c("Omega_input")
if (Use_REML == TRUE)
Random = c(Random, "beta", "ln_VarInfl_NB1", "ln_VarInfl_NB2",
"ln_VarInfl_ZI")
Return = list(Map = Map, Random = Random, Params = Params,
Data = Data, spde = spde)
}
James-Thorson/spatial_factor_analysis documentation built on June 13, 2019, 12:41 p.m.
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Usage
1 | MakeInput_Fn(Version, Y, X, Y_Report = NULL, LastRun = NULL, Loc, isPred, ErrorDist, ObsModel, VaryingKappa, n_factors, n_stations, Use_REML, Aniso)
|
Arguments
Version |
|
Y |
|
X |
|
Y_Report |
|
LastRun |
|
Loc |
|
isPred |
|
ErrorDist |
|
ObsModel |
|
VaryingKappa |
|
n_factors |
|
n_stations |
|
Use_REML |
|
Aniso |
|
mesh |
|
spde |
Examples
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##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (Version, Y, X, Y_Report = NULL, LastRun = NULL, Loc,
isPred, ErrorDist, ObsModel, VaryingKappa, n_factors, n_stations,
Use_REML, Aniso)
{
mesh = inla.mesh.create(Loc[, c("x", "y")], plot.delay = NULL,
refine = FALSE)
spde = inla.spde2.matern(mesh, alpha = 2)
Dset = 1:2
TV = mesh$graph$tv
V0 = mesh$loc[TV[, 1], Dset]
V1 = mesh$loc[TV[, 2], Dset]
V2 = mesh$loc[TV[, 3], Dset]
E0 = V2 - V1
E1 = V0 - V2
E2 = V1 - V0
TmpFn = function(Vec1, Vec2) abs(det(rbind(Vec1, Vec2)))
Tri_Area = rep(NA, nrow(E0))
for (i in 1:length(Tri_Area)) Tri_Area[i] = TmpFn(E0[i, ],
E1[i, ])/2
NAind = ifelse(is.na(Y), 1, 0)
if (is.null(Y_Report))
Y_Report = array(0, dim = dim(Y))
n_species = ncol(Y)
n_fit = nrow(Y)
if (Version == "spatial_factor_analysis_v18")
Data = list(Y = Y_fit, Y_Report = Y_Report, NAind = NAind_fit,
isPred = isPred, ErrorDist = as.integer(2), VaryingKappa = as.integer(VaryingKappa),
n_species = n_species, n_stations = n_fit, n_factors = n_factors,
meshidxloc = mesh$idx$loc - 1, n_p = ncol(X_fit),
X = X_fit, G0 = spde$param.inla$M0, G1 = spde$param.inla$M1,
G2 = spde$param.inla$M2)
if (Version %in% c("spatial_factor_analysis_v19", "spatial_factor_analysis_v20"))
Data = list(Pen_Vec = c(0, 0), Y = Y_fit, Y_Report = Y_Report,
NAind = NAind_fit, isPred = isPred, ErrorDist = as.integer(2),
VaryingKappa = as.integer(VaryingKappa), n_species = n_species,
n_stations = n_fit, n_factors = n_factors, meshidxloc = mesh$idx$loc -
1, n_p = ncol(X_fit), X = X_fit, G0 = spde$param.inla$M0,
G1 = spde$param.inla$M1, G2 = spde$param.inla$M2)
if (Version %in% c("spatial_factor_analysis_v21", "spatial_factor_analysis_v22"))
Data = list(Aniso = as.integer(Aniso), Pen_Vec = c(0,
0), Y = Y_fit, Y_Report = Y_Report, NAind = NAind_fit,
isPred = isPred, ErrorDist = as.integer(2), VaryingKappa = as.integer(VaryingKappa),
n_species = n_species, n_stations = n_fit, n_factors = n_factors,
n_i = mesh$n, meshidxloc = mesh$idx$loc - 1, n_p = ncol(X_fit),
X = X_fit, n_tri = nrow(mesh$graph$tv), Tri_Area = Tri_Area,
E0 = E0, E1 = E1, E2 = E2, TV = TV - 1, G0 = spde$param.inla$M0,
G0_inv = as(diag(1/diag(spde$param.inla$M0)), "dgTMatrix"),
G1 = spde$param.inla$M1, G2 = spde$param.inla$M2)
if (StartValue == "Default" | is.null(LastRun)) {
if (Version %in% c("spatial_factor_analysis_v18", "spatial_factor_analysis_v19"))
Params = list(beta = matrix(0, nrow = ncol(X), ncol = n_species,
byrow = TRUE), Psi_val = rep(1, n_factors * n_species -
n_factors * (n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl = matrix(-2,
nrow = 3, ncol = n_species), Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v20")
Params = list(beta = matrix(0, nrow = ncol(X), ncol = n_species,
byrow = TRUE), Psi_val = rep(1, n_factors * n_species -
n_factors * (n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl_NB1 = NA,
ln_VarInfl_NB2 = NA, ln_VarInfl_ZI = NA, Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v21")
Params = list(ln_H_input = c(0, -10, 0), beta = matrix(0,
nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = rep(1, n_factors * n_species - n_factors *
(n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl_NB1 = NA,
ln_VarInfl_NB2 = NA, ln_VarInfl_ZI = NA, Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v22")
Params = list(ln_H_input = c(0, 0), beta = matrix(0,
nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = rep(1, n_factors * n_species - n_factors *
(n_factors - 1)/2), log_kappa_input = rep(0,
ifelse(VaryingKappa == 0, 1, n_factors)), ln_VarInfl_NB1 = NA,
ln_VarInfl_NB2 = NA, ln_VarInfl_ZI = NA, Omega_input = matrix(rep(0,
spde$n.spde * n_factors), ncol = n_factors))
if (ObsModel == "Poisson") {
Params[["ln_VarInfl_NB1"]] = rep(-20, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin1") {
Params[["ln_VarInfl_NB1"]] = rep(-2, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin12") {
Params[["ln_VarInfl_NB1"]] = rep(-2, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-2, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
}
if (StartValue == "Last_Run" & !is.null(LastRun)) {
Par_last = LastRun$opt$par
Par_best = LastRun$obj$env$last.par.best
if (Version %in% c("spatial_factor_analysis_v18", "spatial_factor_analysis_v19"))
Params = list(beta = matrix(Par_last[which(names(Par_last) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl = Par_last[which(names(Par_last) ==
"ln_VarInfl")], Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v20")
Params = list(beta = matrix(Par_last[which(names(Par_last) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl_NB1 = NA, ln_VarInfl_NB2 = NA,
ln_VarInfl_ZI = NA, Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v21")
Params = list(ln_H_input = Par_last[which(names(Par_last) ==
"ln_H_input")], beta = matrix(Par_last[which(names(Par_last) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl_NB1 = NA, ln_VarInfl_NB2 = NA,
ln_VarInfl_ZI = NA, Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (Version %in% "spatial_factor_analysis_v22")
Params = list(ln_H_input = Par_best[which(names(Par_best) ==
"ln_H_input")], beta = matrix(Par_best[which(names(Par_best) ==
"beta")], nrow = ncol(X), ncol = n_species, byrow = TRUE),
Psi_val = c(Par_last[which(names(Par_last) ==
"Psi_val")], rep(1, n_species - n_factors +
1)), log_kappa_input = c(Par_last[which(names(Par_last) ==
"log_kappa_input")], list(NULL, 1)[[ifelse(VaryingKappa ==
0, 1, 2)]]), ln_VarInfl_NB1 = NA, ln_VarInfl_NB2 = NA,
ln_VarInfl_ZI = NA, Omega_input = matrix(c(Par_best[which(names(Par_best) ==
"Omega_input")], rep(0, spde$n.spde)), ncol = n_factors))
if (ObsModel == "Poisson") {
Params[["ln_VarInfl_NB1"]] = rep(-20, n_species)
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin1") {
Params[["ln_VarInfl_NB1"]] = Par_best[which(names(Par_best) ==
"ln_VarInfl_NB1")]
Params[["ln_VarInfl_NB2"]] = rep(-20, n_species)
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (ObsModel == "NegBin12") {
Params[["ln_VarInfl_NB1"]] = Par_best[which(names(Par_best) ==
"ln_VarInfl_NB1")]
Params[["ln_VarInfl_NB2"]] = Par_best[which(names(Par_best) ==
"ln_VarInfl_NB2")]
Params[["ln_VarInfl_ZI"]] = rep(-20, n_species)
}
if (Version %in% c("spatial_factor_analysis_v20", "spatial_factor_analysis_v21")) {
if (Aniso == 0)
Params[["ln_H_input"]] = c(0, -10, 0)
}
if (Version %in% c("spatial_factor_analysis_v22")) {
if (Aniso == 0)
Params[["ln_H_input"]] = c(0, 0)
}
}
Map = list()
if (ObsModel == "Poisson") {
Map[["ln_VarInfl_NB1"]] = factor(rep(NA, n_species))
Map[["ln_VarInfl_NB2"]] = factor(rep(NA, n_species))
Map[["ln_VarInfl_ZI"]] = factor(rep(NA, n_species))
}
if (ObsModel == "NegBin1") {
Map[["ln_VarInfl_ZI"]] = factor(rep(NA, n_species))
Map[["ln_VarInfl_NB2"]] = factor(rep(NA, n_species))
}
if (ObsModel == "NegBin12") {
Map[["ln_VarInfl_ZI"]] = factor(rep(NA, n_species))
}
if (Version %in% c("spatial_factor_analysis_v18", "spatial_factor_analysis_v19",
"spatial_factor_analysis_v20", "spatial_factor_analysis_v21")) {
if (Aniso == 0)
Map[["ln_H_input"]] = factor(rep(NA, 3))
if (Aniso == 1 & VaryingKappa == 0)
Map[["log_kappa_input"]] = factor(NA)
}
if (Version %in% c("spatial_factor_analysis_v22")) {
if (Aniso == 0)
Map[["ln_H_input"]] = factor(rep(NA, 2))
}
Random = c("Omega_input")
if (Use_REML == TRUE)
Random = c(Random, "beta", "ln_VarInfl_NB1", "ln_VarInfl_NB2",
"ln_VarInfl_ZI")
Return = list(Map = Map, Random = Random, Params = Params,
Data = Data, spde = spde)
}
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