search for: ptacnik

...defined by longitude and latitude (in degrees), and want to calculate the spatial (or geographic) distance among all locations. I did not find such a function in the spatial-related packages. (I *cannot* use 'dist', as I have geographic, not cartesian coordinates). thanks! Robert Robert Ptacnik Norwegian Institute for Water Research (NIVA) Gaustadall?en 21 NO-0349 Oslo mobile +47 982 277 81 FON NIVA +47 22 18 51 00 FAX +47 22 18 52 00 ---------------------------------------------------------------------------------------------------------------------- NIVAs hovedkontor har flyttet ti...

...community of primary producers, y is the productivity of each community; productivity and its predictability both increase with increasing species richness). Apologies for the probably clumsy decription of my problem - I am ecologist, not statistician (but a big fan of R). Cheers, Robert Robert Ptacnik Norwegian Institute for Water Research (NIVA) Gaustadall?en 21 NO-0349 Oslo FON +47 982 277 81 FAX +47 221 852 00

...a better job in predicting Sa than a high resolution grid. However, I wonder if there aren't more elegant ways, e.g. using kriging. Just to avoid misunderstandings: I do not just want to get a spatial grid of Sa and Sb, but I want to find on which Scale Sb affects Sa. cheers, Robert, Robert Ptacnik Norwegian Institute for Water Research (NIVA) Gaustadall?en 21 NO-0349 Oslo FON +47 982 277 81 FAX +47 221 852 00 ---------------------------------------------------------------------------------------------------------------------- NIVAs hovedkontor har flyttet til nye lokaler i CIENS - Fo...

Hi group, I have this type of data x(predictor), y(response), factor (grouping x into many groups, with 6-20 obs/group) I want to fit a linear regression with one common intercept. 'factor' should only modify the slopes, not the intercept. The intercept is expected to be >0. If I use y~ x + factor, I get a different intercept for each factor level, but one slope only if I use y~ x *

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the

dear listers, I use gam (from mgcv) for evaluation of shape and strength of relationships between a response variable and several predictors. How can I interpret the 'F' values viven in the GAM summary? Is it appropriate to treat them in a similar manner as the T-statistics in a linear model, i.e. larger values mean that this variable has a stronger impact than a variable with smaller F?

...t;s.wood en bath.ac.uk> > Subject: Re: [R] interpretation of F-statistics in GAMs > To: r-help en stat.math.ethz.ch > Message-ID: <200706221630.44317.s.wood en bath.ac.uk> > Content-Type: text/plain; charset="iso-8859-1" > > On Friday 15 June 2007 08:06, robert.ptacnik en niva.no wrote: > > dear listers, > > I use gam (from mgcv) for evaluation of shape and strength of relationships > > between a response variable and several predictors. > > How can I interpret the 'F' values viven in the GAM summary? Is it > > appropriate to...