step1_down_basic {AccelStab}R Documentation

Basic version Step1 Down Model

Description

Quickly fit the one-step Šesták–Berggren kinetic model.

Usage

step1_down_basic(
  data,
  y,
  .time,
  K = NULL,
  C = NULL,
  validation = NULL,
  parms = NULL,
  reparameterisation = FALSE,
  zero_order = FALSE,
  ...
)

Arguments

data

Dataframe containing accelerated stability data (required).

y

Name of decreasing variable (e.g. concentration) contained within data (required).

.time

Time variable contained within data (required).

K

Kelvin variable (numeric or column name) (optional).

C

Celsius variable (numeric or column name) (optional).

validation

Validation dummy variable, the column must contain only 1s and 0s, 1 for validation data and 0 for fit data. (column name) (optional).

parms

Starting values for the parameters as a list - k1, k2, k3, and c0.

reparameterisation

Use alternative parameterisation of the one-step model which aims to reduce correlation between k1 and k2.

zero_order

Set kinetic order, k3, to zero (straight lines).

...

Further arguments to passed to minpack.lm.

Details

Fit the one-step Šesták–Berggren kinetic (non-linear) model using accelerated stability data that has been stored in an R data frame. Only the model fit object is returned and a summary of the model fit is printed in the console, allowing for more rapid testing than step1_down(). Kinetic parameters (k1, k2 and, if used, k3) are retained in the model even if one or more of these parameters turn out to be non-significant. Further arguments relating to model fitting, such as setting lower bounds for one or more model parameters, may be passed.

Value

The fit object

Examples

#load antigenicity and potency data.
data(antigenicity)
data(potency)

#Use of the step1_down_basic function with C column defined.
fit1 <- step1_down_basic(data = antigenicity, y = "conc", .time = "time", C = "Celsius")

#Basic use of the step1_down_basic function with K column defined & Validation data segmented out.
fit2 <- step1_down_basic(data = antigenicity, y = "conc", .time = "time", K = "K",
validation = "validA")

#When zero_order = FALSE, the output suggests using zero_order = TRUE for Potency dataset.
fit3 <- step1_down_basic(data = potency, y = "Potency", .time = "Time",C = "Celsius",
  reparameterisation = FALSE, zero_order = TRUE)

#reparameterisation is TRUE.
fit4 <- step1_down_basic(data = antigenicity, y = "conc", .time = "time",C = "Celsius",
  reparameterisation = TRUE)

#Use a custom lower bound for k1 (default is 0).
fit5 <- step1_down_basic(data = potency, y = "Potency", .time = "Time", C = "Celsius",
  reparameterisation = TRUE, zero_order = TRUE, lower = c(-Inf, 0, 0))


[Package AccelStab version 2.2.1 Index]