Calculate confidence intervals for C3 Variable J fitting parameters — confidence_intervals_c3_variable

Calculates confidence intervals for parameters estimated by a C3 A-Ci curve fit. It is rare for users to call this function directly, because it can be automatically applied to each curve when calling fit_c3_variable_j.

Usage

confidence_intervals_c3_variable_j(
    replicate_exdf,
    best_fit_parameters,
    lower = list(),
    upper = list(),
    fit_options = list(),
    sd_A = 1,
    error_threshold_factor = 0.147,
    atp_use = 4.0,
    nadph_use = 8.0,
    curvature_cj = 1.0,
    curvature_cjp = 1.0,
    a_column_name = 'A',
    ci_column_name = 'Ci',
    j_norm_column_name = 'J_norm',
    kc_column_name = 'Kc',
    ko_column_name = 'Ko',
    oxygen_column_name = 'oxygen',
    phips2_column_name = 'PhiPS2',
    qin_column_name = 'Qin',
    rl_norm_column_name = 'RL_norm',
    total_pressure_column_name = 'total_pressure',
    vcmax_norm_column_name = 'Vcmax_norm',
    cj_crossover_min = NA,
    cj_crossover_max = NA,
    hard_constraints = 0,
    require_positive_gmc = 'positive_a',
    gmc_max = Inf
  )

Arguments

replicate_exdf: An exdf object representing one CO2 response curve.
best_fit_parameters: An exdf object representing best-fit parameters for the CO2 response curve in replicate_exdf, as calculated by fit_c3_variable_j.
lower: The same value that was passed to fit_c3_variable_j when generating best_fit_parameters.
upper: The same value that was passed to fit_c3_variable_j when generating best_fit_parameters.
fit_options: The same value that was passed to fit_c3_variable_j when generating best_fit_parameters.
sd_A: The same value that was passed to fit_c3_variable_j when generating best_fit_parameters.
error_threshold_factor: A multiplicative factor that sets the threshold value of the error function used to define the edges of the confidence intervals; see details below.
atp_use: The number of ATP molecules used per C3 cycle.
nadph_use: The number of NADPH molecules used per C3 cycle.
curvature_cj: A dimensionless quadratic curvature parameter greater than or equal to 0 and less than or equal to 1 that sets the degree of co-limitation between Wc and Wj. A value of 1 indicates no co-limitation.
curvature_cjp: A dimensionless quadratic curvature parameter greater than or equal to 0 and less than or equal to 1 that sets the degree of co-limitation between Wcj and Wp. A value of 1 indicates no co-limitation.
a_column_name: The name of the column in replicate_exdf that contains the net assimilation in micromol m^(-2) s^(-1).
ci_column_name: The name of the column in replicate_exdf that contains the intercellular CO2 concentration in micromol mol^(-1).
j_norm_column_name: The name of the column in replicate_exdf that contains the normalized J values (with units of normalized to J at 25 degrees C).
kc_column_name: The name of the column in replicate_exdf that contains the Michaelis-Menten constant for rubisco carboxylation in micromol mol^(-1).
ko_column_name: The name of the column in replicate_exdf that contains the Michaelis-Menten constant for rubisco oxygenation in mmol mol^(-1).
oxygen_column_name: The name of the column in exdf_obj that contains the concentration of O2 in the ambient air, expressed as a percentage (commonly 21% or 2%); the units must be percent.
phips2_column_name: The name of the column in replicate_exdf that contains values of the operating efficiency of photosystem II (dimensionless).
qin_column_name: The name of the column in replicate_exdf that contains values of the incident photosynthetically active flux density in micromol m^(-2) s^(-1).
rl_norm_column_name: The name of the column in replicate_exdf that contains the normalized RL values (with units of normalized to RL at 25 degrees C).
total_pressure_column_name: The name of the column in replicate_exdf that contains the total pressure in bar.
vcmax_norm_column_name: The name of the column in replicate_exdf that contains the normalized Vcmax values (with units of normalized to Vcmax at 25 degrees C).
cj_crossover_min: To be passed to error_function_c3_variable_j.
cj_crossover_max: To be passed to error_function_c3_variable_j.
hard_constraints: To be passed to calculate_c3_assimilation and calculate_c3_variable_j; see those functions for more details.
require_positive_gmc: To be passed to error_function_c3_variable_j.
gmc_max: To be passed to error_function_c3_variable_j.

Details

In maximum likelihood fitting, each set of parameter values has an associated likelihood value. If the maximum likelihood is known, then it is also possible to define a relative likelihood p according to p = L / L_max. The set of all parameter values where p exceeds a threshold value p_0 defines a region in parameter space called like a "relative likelihood region." When taking one-dimensional cuts through parameter space, the boundaries of the relative likelihood region define a relative likelihood interval.

Here we calculate the upper and lower limits of the relative likelihood intervals for each parameter. This is done by fixing the other parameters to their best-fit values, and varying a single parameter to find the interval where the relative likelihood is above the threshold value. If the threshold p_0 is set to 0.147, then these intervals are equivalent to 95% confidence intervals in most situations. See the Wikipedia page about relative likelihood for more information.

If the upper limit of a confidence interval is found to exceed ten times the upper limit specified when fitting that parameter, then the upper limit of the condfidence interval is taken to be infinity.

Value

An exdf object based on best_fit_parameters that contains lower and upper bounds for each parameter; for example, if Vcmax_at_25 was fit, best_fit_parameters will contain new columns called Vcmax_at_25_lower and Vcmax_at_25_upper.

Examples

# \donttest{
# Read an example Licor file included in the PhotoGEA package
licor_file <- read_gasex_file(
  PhotoGEA_example_file_path('c3_aci_1.xlsx')
)

# Define a new column that uniquely identifies each curve
licor_file[, 'species_plot'] <-
  paste(licor_file[, 'species'], '-', licor_file[, 'plot'] )

# Organize the data
licor_file <- organize_response_curve_data(
    licor_file,
    'species_plot',
    c(9, 10, 16),
    'CO2_r_sp'
)

# Calculate the total pressure in the Licor chamber
licor_file <- calculate_total_pressure(licor_file)

# Calculate temperature-dependent values of C3 photosynthetic parameters
licor_file <- calculate_arrhenius(licor_file, c3_arrhenius_bernacchi)

# Fit just one curve from the data set
one_result <- fit_c3_variable_j(
  licor_file[licor_file[, 'species_plot'] == 'tobacco - 1', , TRUE],
  Ca_atmospheric = 420
)

# Calculate confidence limits for the fit parameters
parameters_with_limits <- confidence_intervals_c3_variable_j(
    licor_file[licor_file[, 'species_plot'] == 'tobacco - 1', , TRUE],
    one_result$parameters
)

# View confidence limits and best estimate for Vcmax_at_25
parameters_with_limits[, c('Vcmax_at_25_lower', 'Vcmax_at_25', 'Vcmax_at_25_upper')]
#>   Vcmax_at_25_lower Vcmax_at_25 Vcmax_at_25_upper
#> 1              -Inf    241.6102               Inf
# }