drmte {drcte}

Fitting time-to-event models for seed science

Description

A general platform for the analysis of seed germination/emergence and other time-to-event data in agriculture.

Usage

  drmte(formula, curveid, pmodels, data = NULL, subset, fct,
  start, na.action = na.omit, logDose = NULL, type = "event",
  control = drmteControl(), lowerl = NULL, upperl = NULL, separate = FALSE,
  pshifts = NULL, varcov = NULL)

Arguments

formula

a symbolic description of the model to be fit. I must be in the form 'count ~ start + end', where count is the number of events observed in the interval between 'start' and 'end'. Other variables can be specified after the 'start' and 'end', as needed to fit, e.g. hydro-time or thermal-time models.

curveid

a numeric vector or factor containing the grouping of the data.

pmodels

a data frame with a many columns as there are parameters in the non-linear function. Or a list containing a formula for each parameter in the nonlinear function.

data

an optional data frame containing the variables in the model.

subset

an optional vector specifying a subset of observations to be used in the fitting process.

fct

a list with three or more elements specifying the non-linear function, the accompanying self starter function, the names of the parameter in the non-linear function and, optionally, the first and second derivatives as well as information used for calculation of ED values. Currently available functions include, among others, the four- and five-parameter log-logistic models LL.4, LL.5 and the Weibull model W1.4. Use getMeanFunctions for a full list.

type

a character string specifying the distribution of the data (parameter estimation will depend on the assumed distribution as different log likelihood functions will be used). The default is "event", implying a multinomial distribution.

start

an optional numeric vector containing starting values for all mean parameters in the model. Overrules any self starter function.

na.action

a function for treating mising values ('NA's). Default is na.omit.

logDose

a numeric value or NULL. If log doses value are provided the base of the logarithm should be specified (exp(1) for the natural logarithm and 10 for 10-logarithm).

control

a list of arguments controlling constrained optimisation (zero as boundary), maximum number of iteration in the optimisation, relative tolerance in the optimisation, warnings issued during the optimisation.

lowerl

a numeric vector of lower limits for all parameters in the model (the default corresponds to minus infinity for all parameters).

upperl

a numeric vector of upper limits for all parameters in the model (the default corresponds to plus infinity for all parameters).

separate

logical value indicating whether curves should be fit separately (independent of each other).

pshifts

a matrix of constants to be added to the matrix of parameters. Default is no shift for all parameters.

varcov

an optional user-defined known variance-covariance matrix for the responses. Default is the identity matrix (NULL), corresponding to independent response values with a common standard deviation, which will be estimated from the data.

Details

This function relies on the general optimiser function optim for the minimisation of negative log likelihood function. The control arguments are specified using the function drmc.

Setting lowerl and/or upperl automatically invokes constrained optimisation.

The columns of a data frame argument to pmodels are automatically converted into factors. This does not happen if a list is specified.

Value

An object of class 'drcte' and 'drc'.

Author(s)

Andrea Onofri

Examples

data(verbascum)
modVerb <- drmte(nSeeds ~ timeBef + timeAf, curveid = Species,
             fct = NPMLE(), data = verbascum)