devRateModel function

Compute non-linear regression

Determine the nonlinear least-squares estimates of the parameters of a nonlinear model, on the basis of the nls function from package stats.

devRateModel(eq, temp, devRate, startValues, dfData = NULL, algo = "GN", ...)

Arguments

• eq: The name of the equation. See devRateEqList for the list of equations
• temp: The temperature (vector).
• devRate: The development rate (days)^-1 (vector).
• startValues: Starting values for the regression (list).
• dfData: A data.frame with the temperature in the first column and the development rate in the second column (alternative to the use of temp and devRate).
• algo: The abbreviated name of the algorithm used for model fitting ( "GN" for Gauss-Newton algorithm, "LM" for Levenberg-Marquardt algorithm; "GN" is the default value).
• ...: Additional arguments for the nls function.

Returns

An object of class nls (except for Stinner et al. 1974 and Lamb 1992 where the function returns a list of two objects of class nls).

Details

startValues for equations by Stinner et al. 1974 and Lamb 1992 are composed of two equations: one for the temperatures below the optimal temperature and another for the temperatures above the optimal temperature. For these equations, startValues should be a list of two lists, where the second element only contain starting estimates not specified in the first element, e.g., for Stinner et al.: startValues <- list(list(C = 0.05, k1 = 5, k2 = -0.3), list(Topt = 30)), and for Lamb 1992: startValues <- list(list(Rm = 0.05, Tmax = 35, To = 15), list(T1 = 4))

The temperature should be provided as a vector in argument temp and development rate in another vector in argument devRate. However, it is possible to use the function with a data.frame containing the temperature in the first column and the development rate in the sceond column, using the argument dfData

NULL is returned when an unknown algorithm is entered.

Examples

## Example with a linear model (no starting estimates)
myT <- 5:15
myDev <- -0.05 + rnorm(n = length(myT), mean = myT, sd = 1) * 0.01
myNLS <- devRateModel(
  eq = campbell_74,
  temp = myT,
  devRate = myDev)
## Example with a non-linear model (starting estimates)
myT <- seq(from = 0, to = 50, by = 10)
myDev <- c(0.001, 0.008, 0.02, 0.03, 0.018, 0.004)
myNLS <- devRateModel(
  eq = stinner_74,
  temp = myT,
  devRate = myDev,
  startValues = list(
    list(C = 0.05, k1 = 5, k2 = -0.3),
    list(Topt = 30)))
## Example with a data.frame instead of two vectors for temperature and
## development rate
myDF <- data.frame(myT, myDev)
myNLS <- devRateModel(
  eq = campbell_74,
  dfData = myDF)