sse.sample {fxTWAPLS} | R Documentation |
Calculate Sample Specific Errors
Description
Calculate Sample Specific Errors
Usage
sse.sample(
modern_taxa,
modern_climate,
fossil_taxa,
trainfun,
predictfun,
nboot,
nPLS,
nsig,
usefx = FALSE,
fx_method = "bin",
bin = NA,
cpus = 4,
seed = NULL,
test_mode = FALSE,
test_it = 5
)
Arguments
modern_taxa |
The modern taxa abundance data, each row represents a sampling site, each column represents a taxon. |
modern_climate |
The modern climate value at each sampling site |
fossil_taxa |
Fossil taxa abundance data to reconstruct past climates, each row represents a site to be reconstructed, each column represents a taxon. |
trainfun |
Training function you want to use, either
|
predictfun |
Predict function you want to use: if |
nboot |
The number of bootstrap cycles you want to use. |
nPLS |
The number of components to be extracted. |
nsig |
The significant number of components to use to reconstruct past climates, this can be obtained from the cross-validation results. |
usefx |
Boolean flag on whether or not use |
fx_method |
Binned or p-spline smoothed |
bin |
Binwidth to get fx, needed for both binned and p-splined method.
if |
cpus |
Number of CPUs for simultaneous iterations to execute, check
|
seed |
Seed for reproducibility. |
test_mode |
Boolean flag to execute the function with a limited number
of iterations, |
test_it |
Number of iterations to use in the test mode. |
Value
The bootstrapped standard error for each site.
See Also
fx
, TWAPLS.w
,
TWAPLS.predict.w
, WAPLS.w
, and
WAPLS.predict.w
Examples
## Not run:
# Load modern pollen data
modern_pollen <- read.csv("/path/to/modern_pollen.csv")
# Extract taxa
taxaColMin <- which(colnames(modern_pollen) == "taxa0")
taxaColMax <- which(colnames(modern_pollen) == "taxaN")
taxa <- modern_pollen[, taxaColMin:taxaColMax]
# Load reconstruction data
Holocene <- read.csv("/path/to/Holocene.csv")
taxaColMin <- which(colnames(Holocene) == "taxa0")
taxaColMax <- which(colnames(Holocene) == "taxaN")
core <- Holocene[, taxaColMin:taxaColMax]
## SSE
nboot <- 5 # Recommended 1000
nsig <- 3 # This should be got from the random t-test of the cross validation
sse_tf_Tmin2 <- fxTWAPLS::sse.sample(
modern_taxa = taxa,
modern_climate = modern_pollen$Tmin,
fossil_taxa = core,
trainfun = fxTWAPLS::TWAPLS.w2,
predictfun = fxTWAPLS::TWAPLS.predict.w,
nboot = nboot,
nPLS = 5,
nsig = nsig,
usefx = TRUE,
fx_method = "bin",
bin = 0.02,
cpus = 2,
seed = 1
)
# Run with progress bar
`%>%` <- magrittr::`%>%`
sse_tf_Tmin2 <- fxTWAPLS::sse.sample(
modern_taxa = taxa,
modern_climate = modern_pollen$Tmin,
fossil_taxa = core,
trainfun = fxTWAPLS::TWAPLS.w2,
predictfun = fxTWAPLS::TWAPLS.predict.w,
nboot = nboot,
nPLS = 5,
nsig = nsig,
usefx = TRUE,
fx_method = "bin",
bin = 0.02,
cpus = 2,
seed = 1
) %>% fxTWAPLS::pb()
## End(Not run)