Thanks Rui and everyone for your help!
Using ` constraint = "increase"` and `lambda = 0.1` did it.
If we ignore the first point, `lambda = -1` option is also possible. `cobs`
will automatically choose a lambda value
plot(fit_result)
summary(fit_result)
# COBS smoothing spline (degree = 2) from call:
# cobs(x = dat$x, y = dat$y, constraint = "increase", lambda = -1,
pointwise = con)
# {tau=0.5}-quantile; dimensionality of fit: 29 from {29}
# x$knots[1:9]: -6.0e-06, 2.5e-01, 5.0e-01, ... , 6.0e+00
# lambda = 1.4494, selected via SIC, out of 25 ones.
# with 10 pointwise constraints
# coef[1:11]: -6.1866e-05, 1.1065e+00, 2.7435e+00, 3.1815e+00,
3.7572e+00, ... , 1.9183e+01
# R^2 = 100% ; empirical tau (over all): 5/10 = 0.5 (target tau= 0.5)
Best,
-- Tung
On Wed, Jan 22, 2020 at 9:39 AM Rui Barradas <ruipbarra...@sapo.pt> wrote:
> Hello,
>
> This seems to "work". It doesn't give errors nor warnings and the fitted
> line passes through the given points.
>
>
> fit_result <- cobs(dat$x, dat$y,
> constraint = "increase",
> lambda = 0.1,
> pointwise = con)
>
> plot(y~x, dat)
> pred <- predict(fit_result)
> lines(pred[,1], pred[,2], col = "red")
>
>
> Hope this helps,
>
> Rui Barradas
>
> Às 15:00 de 22/01/20, Tung Nguyen escreveu:
> > Hello R-Help,
> >
> > I'm trying to find the best fitting curve through a given set of points.
> > The fitted curve must also pass through these points. I found an answer
> on
> > Cross Validated which suggested to use the `cobs: Constrained B-Splines
> > (Sparse Matrix Based)` package. However, I got an error while testing it
> > with my sample data:
> >
> > Error in x %*% coefficients: NA/NaN/Inf in foreign function call (arg 2)
> >
> > *My question*: what caused this error and how can I fix it? Any
> suggestion
> > is greatly appreciated. Thanks!
> >
> > library(cobs)
> >
> > dat <- data.frame(
> > x = c(1e-06,0.25,0.5,0.75,1,2,3,4,5,6),
> > y = c(1e-07,1.925,2.9625,3.469375,
> > 3.875,4.5315,4.89,5.09375,5.216,5.46))
> > dat
> > #> x y#> 1 1.0e-06 0.0000001#> 2 2.5e-01
> > 1.9250000#> 3 5.0e-01 2.9625000#> 4 7.5e-01 3.4693750#> 5 1.0e+00
> > 3.8750000#> 6 2.0e+00 4.5315000#> 7 3.0e+00 4.8900000#> 8 4.0e+00
> > 5.0937500#> 9 5.0e+00 5.2160000#> 10 6.0e+00 5.4600000
> > # visual inspection
> > plot(dat); lines(dat)
> >
> > # define constrained points
> > con <- matrix(
> > cbind(c(0,0,0,0,0,0,0,0,0,0),
> > c(1e-06,0.25,0.5,0.75,1,2,3, 4,5,6),
> > c(1e-07,1.925,2.9625,3.469375,
> > 3.875,4.5315,4.89,5.09375,5.216, 5.46)),
> > ncol = 3, nrow = 10)
> > # curve fitting
> > fit_result <- cobs(dat$x, dat$y, pointwise = con)*#> qbsks2():
> > #> Performing general knot selection ...
> > #> Error in x %*% coefficients: NA/NaN/Inf in foreign function call (arg
> 2)*
> >
> >
> > Best regards,
> >
> > -- Tung
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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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