pdr_optimize: Optimize production and consumption parameters for pool...

In PoolDilutionR: Calculate Gross Biogeochemical Flux Rates from Isotope Pool Dilution Data

Optimize production and consumption parameters for pool dilution data

Description

Optimize production and consumption parameters for pool dilution data

Usage

pdr_optimize(
  time,
  m,
  n,
  m_prec,
  ap_prec,
  P,
  k,
  params_to_optimize = c("P", "k"),
  pool = "CH4",
  frac_P = NULL,
  frac_k = NULL,
  other_params = list(),
  cost_fn = pdr_cost,
  prediction_fn = pdr_predict,
  include_progress = FALSE,
  quiet = FALSE
)

Arguments

time	Vector of numeric time values (e.g. days); first should be zero
m	Observed total pool size (as a volume), same length as time
n	Observed heavy isotope (as a volume), same length as time
m_prec	Instrument precision for pool size, expressed as a standard deviation
ap_prec	Instrument precision for atom percent, expressed as a standard deviation
P	production rate, unit gas/unit time
k	first-order rate constant for consumption, 1/unit time
params_to_optimize	Named vector of parameters ("P", "k", "frac_P", and/or "frac_k") to optimize against observations
pool	Name of pool to use when looking up fractionation values if they are not supplied; see pdr_fractionation
frac_P	Fractionation value for production; see pdr_fractionation
frac_k	Fractionation value for consumption; see pdr_fractionation
other_params	Other parameters pass on to optim
cost_fn	Cost function to use; the default is pdr_cost
prediction_fn	Prediction function that the cost function will use; the default is pdr_predict
include_progress	Include detailed optimizer progress data in output?
quiet	Suppress output messages, logical

Value

The output of optim.

Note

Currently there is only one set of fractionation values available in pdr_fractionation, from von Fischer and Hedin (2002, 10.1029/2001GB001448).

See Also

pdr_optimize_df

Examples

tm <- 0:5
m <- c(10, 8, 6, 5, 4, 3)
n <- c(1, 0.7, 0.6, 0.4, 0.3, 0.2)
m_prec <- 0.001
ap_prec <- 0.01

# Optimize values for P (production) and k (consumption), provide starting values for P and k
pdr_optimize(time = tm, m, n, m_prec, ap_prec, P = 0.5, k = 0.3)
# If we don't provide a value for k, it can be estimated from the data
pdr_optimize(tm, m, n, m_prec, ap_prec, P = 0.5)
# Hold k and frac_k constant (ie., k = estimated k0, frac_k = default value), optimize P and frac_P
pdr_optimize(tm, m, n, m_prec, ap_prec, P = 0.5, params_to_optimize = c("P", "frac_P"))
# Optimize only k (provide P and exclude from params_to_optimize)
pdr_optimize(tm, m, n, m_prec, ap_prec, P = 0.5, params_to_optimize = "k")
# Optimize only k, bounding its possible values
op <- list(lower = c("k" = 0.2), upper = c("k" = 0.3))
pdr_optimize(tm, m, n, m_prec, ap_prec, 0.5, 0.27, params_to_optimize = "k", other_params = op)

PoolDilutionR documentation built on Feb. 16, 2023, 10:05 p.m.