platt_modified | R Documentation |
This function enhances the Platt (1980) model by adding parameters not originally included in the model, which were introduced by other models. It also renames parameters to a standardized naming convention used across all models.
platt_modified(model_result)
model_result |
A list containing the results of the model, including parameters such as |
A detailed documentation can be found under https://github.com/biotoolbox/pam?tab=readme-ov-file#platt_modified
A modified model result as a list with the following elements:
etr_type
: ETR Type based on the model result.
etr_regression_data
: Regression data with ETR predictions based on the fitted model.
sdiff
: The difference between observed and predicted ETR values.
a
: Obtained parameter a
, equal to etrmax_without_photoinhibition
.
b
: Obtained parameter b
, equal to alpha
.
c
: Obtained parameter c
, equal to beta
.
d
: Not available, set to NA_real_
.
alpha
: The initial slope of the light curve, transferred unchanged as alpha
.
beta
: The photoinhibition of the light curve, transferred unchanged as beta
.
etrmax_with_photoinhibition
: The maximum electron transport rate with photoinhibition, transferred as pm
.
etrmax_without_photoinhibition
: The maximum electron transport rate without photoinhibition, transferred as ps
.
ik_with_photoinhibition
: PAR where the transition point from light limitation to light saturation is achieved with photoinhibition, transferred as ik
.
ik_without_photoinhibition
: PAR where the transition point from light limitation to light saturation is achieved without photoinhibition, transferred as is
.
im_with_photoinhibition
: The PAR at which the maximum electron transport rate is achieved with photoinhibition, transferred as im
.
w
: Not available, set to NA_real_
.
ib
: Transferred unchanged as ib
.
etrmax_with_without_ratio
: Ratio of etrmax_with_photoinhibition
to etrmax_without_photoinhibition
, and ik_with_photoinhibition
to ik_without_photoinhibition
.
path <- file.path(system.file("extdata", package = "pam"), "20240925.csv")
data <- read_dual_pam_data(path)
result <- platt_generate_regression_ETR_II(data)
modified_result <- platt_modified(result)
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