Re: [R] points overlay axis

) David L Carlson Associate Professor of Anthropology Texas AM University College Station, TX 77840-4352 -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of John Kane Sent: Tuesday, May 14, 2013 7:47 AM To: Jonathan

[R] points overlay axis

Hi, I'm trying to do quite a simple task, but I'm stuck. I've set xaxs = 'i' as I want the origin to be (0,0), but unfortunately I have points that are sat on the axis. R draws the axis over the points, which hides the points somewhat and looks unsightly. Is there any way of getting a point to

[R] list of funtions

Hi, I have a function called fitMicroProtein which takes a value called form, this can be any integer from 0-38. In a larger function I'm making (it's called Newton), the first thing I want to do is construct a list of functions where form is already set. So in pseudocode fs[[1]](...) -

Re: [R] list of funtions

in a loop. I don't think it's something obvious I've missed... On 13 September 2012 18:06, Uwe Ligges lig...@statistik.tu-dortmund.de wrote: On 13.09.2012 19:01, Jonathan Phillips wrote: Hi, I have a function called fitMicroProtein which takes a value called form, this can be any integer from 0-38

[R] constrained optimisation without second order derivatives? - lnsrch error

Hi, I'm trying to do some constrained non-linear optimisation, but my function does not have second order derivatives everywhere. To be a little more specific (the actual function is huge and horrible, so it would probably be better to just describe it) my model has four variables and I'm using

[R] saddle points in optim

Hi, I've been trying to use optim to minimise least squares for a function, and then get a guess at the error using the hessian matrix (calculated from numDeriv::hessian, which I read in some other r-help post was meant to be more accurate than the hessian given in optim). To get the standard

[R] saddle points in optim

Hi, I've been trying to use optim to minimise least squares for a function, and then get a guess at the error using the hessian matrix (calculated from numDeriv::hessian, which I read in some other r-help post was meant to be more accurate than the hessian given in optim). To get the standard