similar to: fit to spike with exponential decay : optim() question

I'm trying to use nls() to fit an exponential decay with an unknown offset in the time (independent variable). (Perhaps this is inherently very difficult?). > decay.pl <- nls (amp ~ expn(b0,b1,tau,t0,t), data = decay, + start = c(b0=1, b1=7.5, tau=3.5, t0=0.1), trace=T) Error in nlsModel(formula, mf, start) : singular gradient matrix at initial parameter estimates

Hi, I'm trying to determine if R is useful to me. I've browsed 'The Basics of S and S-Plus' (Krause & Olson), and like the logic of the language. However, I don't see an easy way to do things like this: * given a set of observations (x,y) (x and y equal-length vectors), and a 2nd set of abscissas x2, interpolate y at the new abscissas x2. (for now, I don't really

First, thanks to all who helped me with my question about rescaling axes on the fly. Using unlist() and range() to set the axis ranges in advance worked well. I've since plotted about 300 datasets with relative ease. Now I'm trying to fit a lossy oscillator resonance to (the square root of) a lorentzian (testframe$y is oscillator amplitude, testframe$x is drive frequency): lorentz

I think this is a bug; at least this behavior is not documented in plot or plot.default. plot.default resets xaxp, and leaves xaxp reset when it exits: par(xaxp=c(0,1,4)) print(par("xaxp")) plot(c(0,1),c(0.2,0.3)) print(par("xaxp")) R. Woodrow Setzer, Jr. Phone: (919) 541-0128 Experimental Toxicology Division

Hello, I have a data set of data which is best fit by an exponential decay function. I would like to use a nonlinear weighted least squares regression. What function should I be using? Thank you! [[alternative HTML version deleted]]

Hello all: I would like to test whether there are treatment effects on decomposition rate, and I would like to inquire about the best, most appropriate means using R. I have plant decomposition data that is generally considered to follow an exponential decay model as follows: Wt = Wi * exp(-k * t) Where Wt and Wi are the weights of the plant material at time t and 0, respectively. k is a

> Sent: Friday, April 06, 2018 at 4:53 AM > From: "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us> > To: "g l" <gnulinux at gmx.com> > coef( graphmodeld ) > coef(graphmodelp) Error: $ operator is invalid for atomic vectors A quick search engine query revealed primarily references to the dollar sign ($) operator which does not seem relevant to this

You did not try my suggestion. You tried David's, which has a leftover mistake from your guesses about what the argument to coef should be. -- Sent from my phone. Please excuse my brevity. On April 6, 2018 3:30:10 AM PDT, g l <gnulinux at gmx.com> wrote: >> Sent: Friday, April 06, 2018 at 4:53 AM >> From: "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us>

> Sent: Friday, April 06, 2018 at 1:44 PM > From: "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us> > > You did not try my suggestion. You tried David's, which has a leftover mistake from your guesses about what the argument to coef should be. Yes, sorry for the mistake. coef(graphmodeld) (Intercept) graphdata[, 1] 4.513544204 -0.006820623 This corresponds

> On Apr 6, 2018, at 3:43 AM, g l <gnulinux at gmx.com> wrote: > >> Sent: Friday, April 06, 2018 at 5:55 AM >> From: "David Winsemius" <dwinsemius at comcast.net> >> >> >> Not correct. You already have `predict`. It is capale of using the `newdata` values to do interpolation with the values of the coefficients in the model. See:

> Sent: Friday, April 06, 2018 at 5:55 AM > From: "David Winsemius" <dwinsemius at comcast.net> > > > Not correct. You already have `predict`. It is capale of using the `newdata` values to do interpolation with the values of the coefficients in the model. See: > > ?predict > The ? details did not mention interpolation explicity; thanks. > The

I have never found the R symbolic differentiation helpful because my functions are typically quite complicated, but was prompted by Steve Ellison's suggestion to try it out in this case: ################# reprex (see reprex package) graphdta <- read.csv( text = "t,c 0,100 40,78 80,59 120,38 160,25 200,21 240,16 280,12 320,10 360,9 400,7 ", header = TRUE ) nd <- c( 100, 250,

Is inbound or outbound? What port? tcp or udp? ------Mensaje original------ De: Bowie Bailey Remitente: centos-bounces at centos.org Para: CentOS mailing list Responder a: CentOS mailing list Asunto: [CentOS] Outbound traffic spike every 30 minutes Enviado: 3 de dic de 2013 19:36 Since Sunday morning, one of my CentOS servers has been generating a small spike of outbound traffic every 30

(I'm new to R) Is there a way to add data to an existing plot, and have the plot axes rescaled automatically (i.e. if the new data lie outside the current axes) ? If not, how can I specify multiple datasets at once, so the axes are scaled to accomodate all sets? Details: (Am I using R's data structures in a reasonable way?) I have many small datasets taken under different

> On Apr 6, 2018, at 8:03 AM, David Winsemius <dwinsemius at comcast.net> wrote: > > >> On Apr 6, 2018, at 3:43 AM, g l <gnulinux at gmx.com> wrote: >> >>> Sent: Friday, April 06, 2018 at 5:55 AM >>> From: "David Winsemius" <dwinsemius at comcast.net> >>> >>> >>> Not correct. You already have

Since Sunday morning, one of my CentOS servers has been generating a small spike of outbound traffic every 30 minutes (X:00 and X:30). It's not enough traffic to really cause any notice except for the fact that it is a very regular pattern and it started abruptly at midnight Sunday. This server is used for mail (Courier-MTA), and DNS (Bind). I cannot find anything unusual in either of

Hi.. I am setting up a new server (2GHz CPU, Ubuntu 8.10) and am using dovecot for an IMAP server. I have installed dovecot 1.1.4 and Squirrelmail 1.4.15. sudo dovecot -n shows this: # 1.1.4: /etc/dovecot/dovecot.conf log_timestamp: %Y-%m-%d %H:%M:%S protocols: imap login_dir: /var/run/dovecot/login login_executable: /usr/lib/dovecot/imap-login login_process_per_connection: no

Hi all, I've uploaded STAR (Spike Train Analysis with R) on CRAN two days ago. The package is designed to analyze neuronal spike (action potential) trains. It uses S3 classes and methods and makes heavy use of other CRAN packages like gss, R2HTML, mgcv, survival. * Analysis of both spontaneous and stimulus evoked activity is implemented for single neuron spike trains as well as for many

Hi all, I've uploaded STAR (Spike Train Analysis with R) on CRAN two days ago. The package is designed to analyze neuronal spike (action potential) trains. It uses S3 classes and methods and makes heavy use of other CRAN packages like gss, R2HTML, mgcv, survival. * Analysis of both spontaneous and stimulus evoked activity is implemented for single neuron spike trains as well as for many

Sorry... Try with some tool to see what type of traffic. (Munin,cacti,ganglia, etc) Is in your lan? Diego Sanchez Sent from my mobile -----Original Message----- From: diegors at gmail.com Date: Tue, 3 Dec 2013 20:42:39 To: CentOS mailing list<centos at centos.org> Reply-To: diegors at gmail.com Subject: Re: [CentOS] Outbound traffic spike every 30 minutes Is inbound or outbound? What