[R] Help needed: gdal-configuration to install sf package in Mac OS Catalina
Hi, I am using R in Mac. I was trying to install sf package but could not and got error. Detail message of error is under this email. It seems like I have to run gdal- configuration, but not sure what that means. Do you have any idea about that? This is the message I got while installing SF package: configure: error: gdal-config not found or not executable. ERROR: configuration failed for package ‘sf’ * removing ‘/Library/Frameworks/R.framework/Versions/3.6/Resources/library/sf’ Error: Failed to install 'sf' from GitHub: (converted from warning) installation of package ‘/var/folders/5_/74nhx31d521cjc_gjz58nh8rgn/T//RtmpO7v2bW/filea6321afd2c24/sf_0.9-1.tar.gz’ had non-zero exit status -- Kind Regards, Bijesh Mishra. *** [[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.
Re: [R] Curve fitting
Generally nlsr package has better reliability in getting parameter estimates because it tries to use automatic derivatives rather than a rather poor numerical estimate, and also uses a Levenberg-Marquardt stabilization of the linearized model. However, nls() can sometimes be a bit more flexible. JN On 2020-04-05 3:20 p.m., Jeff Newmiller wrote: > err... stats::nls... > > On April 5, 2020 12:14:15 PM PDT, Jeff Newmiller > wrote: >> stats::nlm? >> >> On April 5, 2020 11:53:10 AM PDT, Bernard Comcast >> wrote: >>> Any recommendations on an R package to fit data to a nonlinear model >>> Y=f(x) with a single x and y variable? >>> >>> I want to be able to generate parameter uncertainty estimates and >>> prediction uncertainties if possible. >>> >>> Bernard >>> Sent from my iPhone so please excuse the spelling!" >>> __ >>> 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. > __ 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.
Re: [R] Curve fitting
Thanks Jeff Bernard Sent from my iPhone so please excuse the spelling!" > On Apr 5, 2020, at 3:14 PM, Jeff Newmiller wrote: > > stats::nlm? > >> On April 5, 2020 11:53:10 AM PDT, Bernard Comcast >> wrote: >> Any recommendations on an R package to fit data to a nonlinear model >> Y=f(x) with a single x and y variable? >> >> I want to be able to generate parameter uncertainty estimates and >> prediction uncertainties if possible. >> >> Bernard >> Sent from my iPhone so please excuse the spelling!" >> __ >> 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. > > -- > Sent from my phone. Please excuse my brevity. __ 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.
Re: [R] Curve fitting
err... stats::nls... On April 5, 2020 12:14:15 PM PDT, Jeff Newmiller wrote: >stats::nlm? > >On April 5, 2020 11:53:10 AM PDT, Bernard Comcast > wrote: >>Any recommendations on an R package to fit data to a nonlinear model >>Y=f(x) with a single x and y variable? >> >>I want to be able to generate parameter uncertainty estimates and >>prediction uncertainties if possible. >> >>Bernard >>Sent from my iPhone so please excuse the spelling!" >>__ >>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. -- Sent from my phone. Please excuse my brevity. __ 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.
Re: [R] Curve fitting
stats::nlm? On April 5, 2020 11:53:10 AM PDT, Bernard Comcast wrote: >Any recommendations on an R package to fit data to a nonlinear model >Y=f(x) with a single x and y variable? > >I want to be able to generate parameter uncertainty estimates and >prediction uncertainties if possible. > >Bernard >Sent from my iPhone so please excuse the spelling!" >__ >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. -- Sent from my phone. Please excuse my brevity. __ 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.
[R] Curve fitting
Any recommendations on an R package to fit data to a nonlinear model Y=f(x) with a single x and y variable? I want to be able to generate parameter uncertainty estimates and prediction uncertainties if possible. Bernard Sent from my iPhone so please excuse the spelling!" __ 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.
Re: [R] ggplot stat smooth and poly
On Thu, Apr 2, 2020 at 6:10 PM PIKAL Petr wrote:
> Dear all
>
> I am not sure, but I believe that in past it was possible to add smoothing
> lines in ggplot even if some group did not have enough points to perform
> calculation (although I did not find any version which could deliver it).
>
> Here is the code and data
>
> library(ggplot2)
> p <- ggplot(test, aes(x=one, y=two, colour=three))
> p+geom_point(size=5)+stat_smooth(method="lm")
> ***line added to each group
>
> p+geom_point(size=5)+stat_smooth(method="lm", formula=y~poly(x,2))
> Warning message:
> Computation failed in `stat_smooth()`:
> 'degree' must be less than number of unique points
> ***no line added to any group
>
> test <- structure(list(one = 1:20, two = c(1L, 4L, 9L, 16L, 25L, 36L,
> 49L, 64L, 81L, 100L, 121L, 144L, 169L, 196L, 225L, 256L, 289L,
> 324L, 361L, 400L), three = c("a", "a", "a", "a", "b", "b", "b",
> "b", "c", "c", "c", "c", "c", "d", "d", "e", "e", "e", "e", "e"
> )), class = "data.frame", row.names = c(NA, -20L))
>
> My question:
> Is it possible to add smoothing line just to the groups where it can be
> added? I know that I could exclude "d" level from my data but I would
> prefer
> to keep them and add only smoothing lines where they could be computed.
>
Looks like there's a tryCatch around each panel, but not for each group
within panel. So this would work:
p + geom_point(size=2) + facet_wrap(~three) +
stat_smooth(method="lm", formula=y~poly(x,2))
but one problematic group is enough to make a whole panel fail.
Other than rewriting StatSmooth$compute_panel to protect each per-group
call, a workaround could be to replace method="lm" by a safe wrapper, e.g.,:
plm <- function(formula, data, ...)
{
ocall <- match.call(expand.dots = TRUE)
ocall[[1]] <- quote(lm)
fm <- try(eval(ocall, parent.frame()), silent = TRUE)
if (inherits(fm, "try-error"))
{
ocall[[2]] <- y ~ x
fm <- eval(ocall, parent.frame())
}
fm
}
p + geom_point(size=2) + stat_smooth(method=plm, formula=y~poly(x,2))
-Deepayan
Best regards
> Petr
> __
> 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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