Re: [R] Optimisation with Normalisation Constraint

2018-06-20 Thread David Winsemius
> On Jun 20, 2018, at 8:50 AM, Lorenzo Isella wrote: > > Dear All, > I have a problem I haver been struggling with for a while: I need to > carry out a non-linear fit (and this is the > easy part). > I have a set of discrete values {x1,x2...xN} and the corresponding > {y1, y2...yN}. The

Re: [R] Optimisation with Normalisation Constraint

2018-06-20 Thread Jeff Newmiller
I recommend posting this on a mathematics discussion forum like Stack Exchange and (re-)reading the Posting Guide for this mailing list. I think you are going to need to re-write your model function to algebraically combine your original model along with the constraint, and then use the

Re: [R] Any Unsupervised Learning Algorithm for Time Series Forecasting in R

2018-06-20 Thread Hasan Diwan
Paul, On Wed, 20 Jun 2018 at 09:04, Paul Bernal wrote: > I would like to know if R has any unsupervised algorithm to generate > forecasts for historical data. Yes , it does. Perhaps you'd be kind enough to provide a sample of your data --dput(sample(pauls.data)) on gist.github.com -- and what

Re: [R] Any Unsupervised Learning Algorithm for Time Series Forecasting in R

2018-06-20 Thread Bert Gunter
... and II should have added that the "forecast" package may be what you're looking for. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed,

Re: [R] Any Unsupervised Learning Algorithm for Time Series Forecasting in R

2018-06-20 Thread Bert Gunter
Depending on exactly what you mean by"unsupervised", many. See here under "Decomposition and filtering": https://cran.r-project.org/web/views/TimeSeries.html You could also search on something like "smooth time series R" etc. However, assuming I have correcty interpreted "unsupervised

[R] Any Unsupervised Learning Algorithm for Time Series Forecasting in R

2018-06-20 Thread Paul Bernal
Dear friends, Hope you are all doing great. I would like to know if R has any unsupervised algorithm to generate forecasts for historical data. Any help will be greatly appreciated, Best regards, Paul [[alternative HTML version deleted]] __

[R] Optimisation with Normalisation Constraint

2018-06-20 Thread Lorenzo Isella
Dear All, I have a problem I haver been struggling with for a while: I need to carry out a non-linear fit (and this is the easy part). I have a set of discrete values {x1,x2...xN} and the corresponding {y1, y2...yN}. The difficulty is that I would like the linear fit to preserve the sum of the

Re: [R-es] Paquete dismo, cálculo coeficiente de variación

2018-06-20 Thread Marcelino de la Cruz Rot
Hola Jaume: Lo más rápido para ver el código, al ser un método S4 es escribir:  findMethods(biovars) La descripción de la función (con las definiciones y comentarios si los tuviese) los tendrías que ver rebuscando en el código fuente del paquete. Generalmente  en la carpeta "R" del paquete

Re: [R] Extract function parameters from a R expression

2018-06-20 Thread Gabor Grothendieck
If you specifically want to know which packages were loaded by the script then using a vanilla version of R (i.e. one where only base packages are loaded): vanilla_search <- search() source("myRprg.R") setdiff(search(), vanilla_search) On Wed, Jun 20, 2018 at 4:08 AM, Sigbert Klinke

Re: [R] interpret a p-value result as a significance of a linear regression in terms of sigmas

2018-06-20 Thread Peter Dalgaard
Sorry to say so, but you seem confused. The "sigma" in physics parlance is presumably the s.e. of the estimate so the "number of sigmas" equal the t statistic, in this case 5.738. However, use of that measure ignores the t distribution, effectively assuming that there are infinite df (and 24

Re: [R] interpret a p-value result as a significance of a linear regression in terms of sigmas

2018-06-20 Thread Duncan Murdoch
On 20/06/2018 6:53 AM, jean-philippe wrote: dear R community, I am running a linear regression for my dataset between 2 variables (disk mass and velocities). This is the result returned by the summary function onto the lm object for one of my dataset. Call: lm(formula = df$md1 ~ df$logV, data

Re: [R] Extract function parameters from a R expression

2018-06-20 Thread Bert Gunter
... or if the argument is just quoted text or a numeric value as in your library() example, don't parse the text and use regex's to search for the function call and pick out the text of the arguments. Again, this only works (I think) for the simple sort of case of your example. Beyond that,

[R] interpret a p-value result as a significance of a linear regression in terms of sigmas

2018-06-20 Thread jean-philippe
dear R community, I am running a linear regression for my dataset between 2 variables (disk mass and velocities). This is the result returned by the summary function onto the lm object for one of my dataset. Call: lm(formula = df$md1 ~ df$logV, data = df) Residuals: Min 1Q

Re: [R] Extract function parameters from a R expression

2018-06-20 Thread Hadley Wickham
You need to recursively walk the parse tree/AST. See, e.g., https://adv-r.hadley.nz/expressions.html#ast-funs Hadley On Wed, Jun 20, 2018 at 10:08 AM, Sigbert Klinke wrote: > Hi, > > I have read an R program with > > expr <- parse("myRprg.R") > > How can I extract the parameters of a specifc R

[R] Extract function parameters from a R expression

2018-06-20 Thread Sigbert Klinke
Hi, I have read an R program with expr <- parse("myRprg.R") How can I extract the parameters of a specifc R command, e.g. "library"? So, if myprg.R containes the lines library("xyz") library("abc") then I would like to get "xyz" and "abc" back from expr. Thanks in advance Sigbert --