similar to: relative importance of predictors

Hi, I have a set of locations 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

Hei, I have two spatial datasets Sa and Sb, both with lat-lon coordinates and from same geographic area, but from different localities within the area (independent samples). Sa is biotoc data, Sb is some environmental parameter (fertility). I 'know' that Sb affects Sa, but wonder on which scale. I tried different interpolations by creating different grids of Sb (e.g. 20x20 and 100x100

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 *

Hello, Is there a simple way of stacking/merging two dataframes in R? I want to stack them piece-wise, not simply add one whole dataframe to the bottom of the other. I want to create as follows: x.frame: aX1 bX1 cX1 ... zX1 aX2 bX2 cX2 ... zX2 ... ... ... ... ... aX99 bX99 cX99 ... zX99 y.frame: aY1 bY1 cY1 ... zY1 aY2 bY2 cY2 ... zY2 ... ... ... ... ... aY99 bY99 cY99 ...

Dear all, I am stuck with tracking down an error I get from R CMD check (Windows, R 2.4.0, same error for R 2.2.1): when running R CMD check over a modified version of package relaimpo, I get the following output in install.out: preparing package relaimpo for lazy loading Loading required package: MASS Loading required package: boot Error in parse(file, n, text, prompt) : syntax error at 2193:

I'm having trouble getting the relaimpo package to use a covariance matrix as input. I'm getting an error message that reads as follows: Error in eval(m$weights, data, parent.frame()) : numeric 'envir' arg not of length one I'm guessing there is something wrong with the structure of my covariance matrix, but it looks fine to me. Pardon my R ignorance if this is an easy

Dear R-developers, I'm experiencing a problem with having an example run under R 2.6.1 RC (downloaded and installed today, r43513), which does not occur on R 2.6.0: The new version of package relaimpo does list package survey under "Depends", and an example directly (i.e. not only from within a function of relaimpo) uses function svydesign from package survey. Package survey is

Dear all: Y=a+bX1+cX2 In the Gee (Generalized Estimation Equation) arguments: The arument Corstr has sveral choices: "independence" "fixed" "stat_M_dep" "non_stat_M_dep" "exchangeable" "AR-M" "unstructured" What does each term mean? How do I choose among them? How do I know the correlation structure of

I have a program which is doing a few thousand runs of lm(). Suppose it is a simple model y = a + bx1 + cx2 + e I have the R object "d" where d <- summary(lm(y ~ x1 + x2)) I would like to obtain Var(x2) out of "d". How might I do it? I can, of course, always do sd(x2). But it would be much more convenient if I could snoop around the contents of summary.lm and

Dear developeRs, with R 2.4.1 (and also 2.4.0), the function str() fails on objects of class relimplmbooteval, if there are unused slots, which is very often the case. I am not sure whether this is a bug in str() or a correct behavior of str() that unmasks some sloppiness in my usage of S4 classes (that I am not aware of)? Reproducible example (package relaimpo needed): The program

Dear Listers, I have a regression problem (x->y) with biological data, where x influences y in two ways, (1) y increases with x and (2) the variation around the mean (residuals) decreases with increasing x, i.e. y becomes more 'predictable' as x increases. The relationship is saturating, y~a + bx + cx^2, gives a very good fit. I know basically how to test for heteroscedasticity. My

Is there a painless way to find the names of all packages on CRAN that "Depend" on a specified package? url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820

Dear all , Is there any subset regression (subset selection regression) package in R other than "leaps"? Thanks and regards Alex [[alternative HTML version deleted]]

Hello! I am trying test my observed data against the null-hypothesis that different items from a psychological questionnaire contribute equally to the metric dependent variable that measures problems (sum score of a questionnaire). That is, I am interested in relative strength of the predictors. Predictor items of the questionnaire are on a scale from 0-3, and technically ordinal, although most

Dear All: I am calculating the relative importance of a regressor in a linear model. Does anyone know how I can obtain/install the 'pmvd' computation type? I am a US user. Regards, Y -- View this message in context: http://r.789695.n4.nabble.com/calc-relimp-pmvd-for-US-R-user-tp3808752p3808752.html Sent from the R help mailing list archive at Nabble.com.

Hello, I would like to know what it means, when the hier.part's output has a data frame of a negative independent contribution for variables (?IJ) and how this can be caused. Thank you very much. Yours sincerely M. Heuner

Hi, I would like to perform a forward selection procedure on a data set with 6 observations and 10 predictors. I tried to run it with regsubsets (I set nvmax=number of observations) but I keep getting these warning messages: Warning messages: 1: 5 linear dependencies found in: leaps.setup(x, y, wt = weights, nbest = nbest, nvmax = nvmax, 2: nvmax reduced to 5 in: leaps.setup(x, y, wt =

Hi R-Users, I have a student doing work with lionfish and she has been trying to analyse a multivariate dataset to see what variables/factors are influencing the behaviour of lionfish. We have attempted a number of analyses, including rpart, relimpo and standard linear regression but we are not having much luck with quality output. The data is very non-normal and we would appreciate some advice

I have installed the latest relaimpo library ( form their website with the 8 functions) When running pvmd as a type in c=type("pmvd") in calc.relimp I get the error message ...could not find function "pmvdcalc" (this is in R version 2.12.1) Can anyone help? Paul Prof P Rheeder School of Health Systems and Public Health Faculty of Health Sciences University of Pretoria Room

I am currently using the relaimpo package to estimate the relative importance of regressors (N= 4000): > m1 <- lm(y ~ x1+x2+x3+x4+x5+, data=data) > calc.relimp(m1, rela=TRUE) > m2=boot.relimp(m1, boot = 500, rela=TRUE, type="lmg") > booteval.relimp(m2) > plot(booteval.relimp(m2)) In a new dataset with 3 measurement points (0,6,12 weeks), I want to perform a similar