step1_sample_mvt {AccelStab}

Sample the Multivariate t Distribution

Description

Take a selected number of samples from the multivariate t distribution (mvt).

Usage

step1_sample_mvt(
  data,
  y,
  .time,
  K = NULL,
  C = NULL,
  validation = NULL,
  draw,
  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 (column name) (optional).

draw

Number of samples to draw from mvt (required).

parms

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

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).

Details

Using the provided data the function creates a fit of the Šesták–Berggren kinetic model and then draws a selected number of samples from the mvt of the model parameters.

Value

A matrix containing parameter draws from the mvt distribution.

Examples

#load antigenicity data.
data(antigenicity)

#Basic use of the step1_sample_mvt function with C column defined and 1000 draws.
sample1 <- step1_sample_mvt(data = antigenicity, y = "conc", .time = "time",
 C = "Celsius", draw = 1000)

#Basic use of the step1_sample_mvt function with K column defined and 50000 draws
sample2 <- step1_sample_mvt(data = antigenicity, y = "conc", .time = "time",
 K = "K", draw = 50000)

#reparameterisation is TRUE and 10000 draws.
sample3 <- step1_sample_mvt(data = antigenicity, y = "conc", .time = "time",
C = "Celsius", reparameterisation = TRUE, draw = 10000)