R Under development (unstable) (2025-08-19 r88650 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> ### Testing function for confidence intervals
> require(ggplot2)
Loading required package: ggplot2
> require(nlraa)
Loading required package: nlraa
> require(nlme)
Loading required package: nlme
> 
> ### Testing objects of class 'lm'
> if(FALSE){
+   set.seed(123)
+   x <- 1:30
+   y <- linp(x, 0, 1, 20) + rnorm(30, 0, 0.5)
+   dat <- data.frame(x = x, y = y)
+   fit.lm <- lm(y ~ x + I(x^2), data = dat)
+   
+   cfs.int <- confidence_intervals(fit.lm)
+   cfs.int <- confidence_intervals(fit.lm, method = c("wald", "bootstrap"))
+   
+   ggplot(data = cfs.int) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")
+   
+   #### Fitting objects of class 'nls'
+   fit.nls <- nls(y ~ SSlinp(x, a, b, xs), data = dat)
+   
+   cfs.int <- confidence_intervals(fit.nls)
+   cfs.int <- confidence_intervals(fit.nls, method = c("wald", "profile", "bootstrap"))
+   
+   ggplot(data = cfs.int) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")
+   
+   data(barley, package = "nlraa")
+   ## Fit a linear model (quadratic)
+   fit.lm <- lm(yield ~ NF + I(NF^2), data = barley)
+   
+   cfs.int <- confidence_intervals(fit.lm, method = c("wald", "bootstrap"))
+   
+   fit.nls <- nls(yield ~ SSlinp(NF, a, b, xs), data = barley)
+   
+   cfs.int2 <- confidence_intervals(fit.nls, 
+                                    R = 2e3,
+                                    method = c("wald", "profile", "bootstrap"))
+   
+   ggplot(data = cfs.int2) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")
+   
+   fit.gls <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary,
+                  correlation = corAR1(form = ~ 1 | Mare))     
+   
+   cfs.int3 <- confidence_intervals(fit.gls, 
+                                    R = 2e3,
+                                    method = c("wald", "bootstrap"))
+   
+   ggplot(data = cfs.int3) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")
+   
+   fit.gnls <- gnls(weight ~ SSlogis(Time, Asym, xmid, scal), Soybean,
+                    weights = varPower())
+   
+   cfs.int4 <- confidence_intervals(fit.gnls, 
+                                    R = 2e3,
+                                    method = c("wald", "bootstrap"))
+   
+   cfs.int4 <- confidence_intervals(fit.gnls, 
+                                    R = 2e3,
+                                    method = "all")
+   
+   ggplot(data = cfs.int4) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")
+   
+   ### Testing lme
+   fit.lme <- lme(distance ~ age, data = Orthodont)
+   
+   cfs.int5 <- confidence_intervals(fit.lme, 
+                                    R = 2e3,
+                                    method = "all")
+   
+   ggplot(data = cfs.int5) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")
+   
+   fit.nlme <- nlme(height ~ SSasymp(age, Asym, R0, lrc),
+                    data = Loblolly,
+                    fixed = Asym + R0 + lrc ~ 1,
+                    random = Asym ~ 1,
+                    start = c(Asym = 103, R0 = -8.5, lrc = -3.3))
+   
+   cfs.int6 <- confidence_intervals(fit.nlme, 
+                                    R = 2e3,
+                                    method = "all")
+   
+   ggplot(data = cfs.int6) + 
+     facet_wrap(~ parm, scales = "free") + 
+     geom_point(aes(x = method, y = lower)) + 
+     geom_point(aes(x = method, y = estimate), color = "red") + 
+     geom_point(aes(x = method, y = upper)) + 
+     ylab("Parameter values")  
+ }
> 
> 
> proc.time()
   user  system elapsed 
   2.39    0.37    2.75