jorischau / gslnls Goto Github PK

library(propagate)
library(minpack.lm)
library(gslnls)


data(Puromycin, package = "datasets")
Puromycin2 <- Puromycin[Puromycin$state == "treated", ][, 1:2]

# nls
Puro.nls <- nls(rate ~ Vm * conc/(K + conc), data = Puromycin2,
                start = c(Vm = 200, K = 0.05))
pred_nls <- predictNLS(Puro.nls, interval = "prediction", 
                       newdata = data.frame(conc = Puromycin$conc), 
                       alpha = 0.05, nsim = 10000)

# minpack.lm
Puro.nlsLM <- nlsLM(rate ~ Vm * conc/(K + conc), data = Puromycin2,
                start = c(Vm = 200, K = 0.05))
pred_nlsLM <- predictNLS(Puro.nlsLM, interval = "prediction", 
                       newdata = data.frame(conc = Puromycin$conc), 
                       alpha = 0.05, nsim = 10000)

# gslnls
Puro.gslnls <- gsl_nls(rate ~ Vm * conc/(K + conc), data = Puromycin2,
                start = c(Vm = 200, K = 0.05))
pred_gslnls <- predictNLS(Puro.gslnls, interval = "prediction", 
                       newdata = data.frame(conc = Puromycin$conc), 
                       alpha = 0.05, nsim = 10000)
#> Error in as.list(eval(model$call$formula))[[3]]: subscript out of bounds


Puro.nls$call$formula
#> rate ~ Vm * conc/(K + conc)
Puro.nlsLM$call$formula
#> rate ~ Vm * conc/(K + conc)

Puro.gslnls$call$formula
#> NULL
Puro.gslnls$call$fn
#> rate ~ Vm * conc/(K + conc)

n <- 50
xy <- data.frame(
  x = (1:n) / n,
  y = 2.5 * exp(-1.5 * (1:n) / n) + 1 + rnorm(n, sd = 0.1)
)
fit <- gsl_nls(y ~ A * exp(-lam * x), data = xy, start = c(A = 1, lam = 1))
confint(fit)
#>       2.5 %    97.5 %
#> 1 3.2817373 3.4308953
#> 2 0.7681381 0.8634295

confint(fit, method = "profile")
#> Waiting for profiling to be done...
#>          2.5%     97.5%
#> A   3.3208899 3.4727355
#> lam 0.8169809 0.9146047