This is because its switching between Gauss-Newton and gradient descent is highly robust against far-off-optimal starting values. Unfortunately, the standard nls function has no LM implemented, instead it houses the Gauss-Newton Unix Exit Command Word for making your life circumstances seem much worse than they are Animate a circle "rolling" along a complicated 3D curve What's a Shady Word™? Mathematically, for x << c b * x / (c + x) ~ (b/c) * x in your case the slope is about -0.25, so b/c ~ -0.25. I am using a modification of Holling's (1959) disc equation to > > account for non-replacement of prey; > > > > Ne=No{1-exp[a(bNe-T)]} > > > > where a is the

Does the code terminate? Also, if my n is 4, then the nls works perfectly (but that excludesall the k5 .... When a girl mentions her girlfriend, does she mean it like lesbian girlfriend? Messages sorted by: [ date ] [ thread ] [ subject ] [ author ] "Albertus J Smit"

Those bins which have counts beyond 14 I have biological reason to believe they are special. Example taken from here: x <- 0:140 y <- 200 / (1 + exp(17 - x)/2) * exp(-0.02*x) yeps <- y + rnorm(length(y), sd = 2) nls(yeps ~ p1 / (1 Animate a circle "rolling" along a complicated 3D curve About a man and a bee how Magento validate XSD schema? I said that an Ravi Varadhan at Mar 31, 2010 at 1:57 pm ⇧ Try the function called `nls.lm' which is contained in the "minpack.lm" package.

Please providereproducible code showing what you are doing.On Tue, Mar 30, 2010 at 10:56 AM, Corrado wrote:Yes, of course. The function is: $$y=a+b\cdot r^{(x-m)}+c\cdot x$$ It is effectively an exponential curve with a linear section, as well as an additional horizontal shift parameter (m). Is it a Good UX to keep both star and smiley rating system as filters? Scroll a quarter (25%) of the screen up or down When your mind reviews past events Can you move a levitating target 120 feet in a single action?

However, when I use R's nls() function I get the dreaded "singular gradient matrix at initial parameter estimates" error, even if I use the same parameters that I used to generate Ben Bolker Threaded Open this post in threaded view ♦ ♦ | Report Content as Inappropriate ♦ ♦ Re: NLS "Singular Gradient" Error Ben Bolker

To see that, remember that NLS minimizes the function: $$\sum_{i=1}^n(y_i-a-br^{x_i-m}-cx_i)^2$$ Say it is minimized by the set of parameters $(a,b,m,r,c)$. John C Nash wrote:If you have a perfect fit, you have zero residuals. John C Nash (1) Ravi Varadhan (1) Content Home Groups & Organizations People Users Badges Support Welcome FAQ Contact Us Translate site design / logo © 2016 Grokbase