library(nlme)
m2 <- gnls(conc ~ t1*(1-t2*exp(-k*time)),
data = df.Chloride,
start = list(
t1 = 35,
t2 = 0.91,
k = 0.22))
summary(m2)
plot(m2)
lag.plot(resid(m2), do.lines=FALSE)
acf(resid(m2))
m3 <- update(m2, corr=corAR1(.67))
summary(m3)
plot(m3)
lag.plot(resid(m3), do.lines=FALSE)
acf(resid(m3))
The residual plots for model m3 still show structure, unlike in Bates &
Watts, so maybe this is not the correct model?
Kevin
On Thu, Aug 13, 2009 at 6:11 AM, Ottorino-Luca Pantani <
[email protected]> wrote:
> Hi R users,
> I'm here trying to understand correlated residuals in nonlinear estimation.
>
> I'm reading/studying the book Bates, D. M. and D. G. Watts, (1988),
> /Nonlinear regression analysis and its applications/, Wiley, NY. pages
> 92-94, trying to reproduce the figures and to find out the code in R to
> perform the necessary calculations.
> I also consulted Pinheiro and Bates, but without success
>
> Here below you'll find are my efforts.
> I'm in trouble at plotting the lag plot (fig 3.6 b) and in fitting the new
> model with autocorrelated residuals (most probably misusing "correlation =
> corAR1()" in updating a nls model).
>
> Could someone be so kind to help me ?
>
> Thanks a lot
> Ottorino
>
> "df.Chloride"<-
> structure(.Data = list(time = c(2.45, 2.55, 2.65, 2.75, 2.85, 2.95, 3.05,
> 3.15,
> 3.25, 3.35, 3.45, 3.55, 3.65, 3.75, 3.85, 3.95, 4.05, 4.15, 4.25, 4.35,
> 4.45, 4.55, 4.65, 4.75, 4.85, 4.95, 5.05, 5.15, 5.25, 5.35, 5.45, 5.55,
> 5.65, 5.75, 5.85, 5.95, 6.05, 6.15, 6.25, 6.35, 6.45, 6.55, 6.65, 6.75,
> 6.85, 6.95, 7.05, 7.15, 7.25, 7.35, 7.45, 7.55, 7.65, 7.75), conc = c(
> 17.3, 17.6, 17.9, 18.3, 18.5, 18.9, 19, 19.3, 19.8, 19.9, 20.2, 20.5,
> 20.6, 21.1, 21.5, 21.9, 22, 22.3, 22.6, 22.8, 23, 23.2, 23.4, 23.7,
> 24, 24.2, 24.5, 25, 25.4, 25.5, 25.9, 25.9, 26.3, 26.2, 26.5, 26.5,
> 26.6, 27, 27, 27, 27, 27.3, 27.8, 28.1, 28.1, 28.1, 28.4, 28.6, 29,
> 29.2, 29.3, 29.4, 29.4, 29.4)), row.names = c("1", "2", "3", "4", "5",
> "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
> "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29",
> "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41",
> "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53",
> "54"), class = "data.frame", reference = "A1.9, p. 274")
>
> ##Figure 3.5, pag 92
> plot(df.Chloride$time, df.Chloride$conc, pch = 20)
>
> ## fitting the model
> nls.1 <- nls(conc ~ t1*(1-t2*exp(-k*time)),
> data = df.Chloride,
> start = list(
> t1 = 35,
> t2 = 0.91,
> k = 0.22))
>
> ##Figure 3.56a, pag 93
> plot(nls.1, pch = 20)
>
> ##Figure 3.56b, pag 93
> ???????????not the foggiest idea
>
> ##Figure 3.57, pag 94
> acf(resid(nls.1), xlim = c(1, 15), lab = c(5, 4, 7))
>
> ##Try to fit a model with autocorrelated residues (Problems !!)
> nls.2 <- update(nls.1, corr = corAR1(0.67))
>
> --
> Ottorino-Luca Pantani, Università di Firenze
> Dip. Scienza del Suolo e Nutrizione della Pianta
> P.zle Cascine 28 50144 Firenze Italia
> Tel 39 055 3288 202 (348 lab) Fax 39 055 333 273 [email protected]
> http://www4.unifi.it/dssnp/
>
> ______________________________________________
> [email protected] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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