similar to: Question about linear regression in R

This command cdmoutcome<- glm(log(value)~factor(year) > +log(gdppcpppconst)+log(gdppcpppconstAII) > +log(co2eemisspc)+log(co2eemisspcAII) > +log(dist) > +fdiboth > +odapartnertohost > +corrupt > +log(infraindex) > +litrate > +africa >

Hello. Consider the response-variable of data.frame df is constant, so analytically perfect fit of a linear model is expected. Fitting a regression line using lm result in residuals, slope and std.errors not exactly zero, which is acceptable in some way, but errorneous. But if you use summary.lm it shows inacceptable error propagation in the calculation of the t value and the corresponding

Hi, I'm trying to match peaks between chromatographic runs. I'm able to match peaks when they are chromatographed with the same method, but not when there are different methods are used and spectra comes in to play. While searching I found the ALS package which should be usefull for my application, but I couldn't figure it out. I made some dummy chroms with R, which mimic my actual

Dear all, I am a relative novice with R, so please forgive any terrible errors... I am working with a GLM that describes a response variable as a function of a categorical variable with three levels and a continuous variable. These two predictor variables are believed to interact. An example of such a model follows at the bottom of this message, but here is a section of its summary table:

> tmp <- data.frame(y=rnorm(12), a=factor(rep(letters[1:4],3))) > tmp y a 1 -0.60866099 a 2 0.55500538 b 3 0.12231693 c 4 -0.24613790 d 5 -0.09253593 a 6 -1.54652581 b 7 0.17204210 c 8 -1.22778942 d 9 1.22151194 a 10 -0.43982577 b 11 -1.25444287 c 12 -0.97251060 d > tmp.aov <- aov(y ~ a, data=tmp) > summary(tmp.aov) Df Sum Sq Mean Sq F value

Dear List, I have a problem I'm finding it difficult to make headway with. Say I have 6 ordered observations, and I want to find all combinations of splitting these 6 ordered observations in g groups, where g = 1, ..., 6. Groups can only be formed by adjacent observations, so observations 1 and 4 can't be in a group on their own, only if 1,2,3&4 are all in the group. For example,

I've recently come across the following results reported from the lm() function when applied to a particular type of admittedly difficult data. When working with small data sets (for instance 3 points) with the same response for different predicting variable, the resulting slope estimate is a reasonable approximation of the expected 0.0, but the p-value of that slope estimate is a surprising

Hi there, I'm quite new to R (and statistics), and I like it (both)! But I'm a bit lost in all these packages, so could someone please give me a hint whether there exists a package for fitting exponential curves (of the type t --> \sum_i a_i \exp( - b_i t)) on a noisy signal? In fact monoexponential decay + polynomial growth is what I'd like to try. Thanks in advance,

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474

Hi R Users, I created interaction plots in ggplot2 and was trying to add output of two way ANOVA models, especially only interaction ( example treatment*control F(XX, XX) = xxx, p = xxx) into figures, but i was not able to add. Would you mind to help on how I can add information into each figure? I have attached the example data and the code that I used for this. dat<-structure(list(Sites

Hi, I am new in statistics and i manage to make the linear model analysis but i have some difficulties in explaining the results. Can someone help me explalinig the output of my linear model analysis ? My data are with 2 variables habitat (e,s) and treatment (a,c,p) with multiple trials within. Thank you in advance Call: lm(formula = a$wild ~ a$habitat/a$treatment/a$trial) Residuals: Min

Dear All, I need to separate one column which is in a format like, "can_region", into two columns like, "can", and "region". Do we have a function in R to do this? Thanks. Regards, Jin [[alternative HTML version deleted]]

Hi, r-users I got a problem when I try to call a *gls* function in loop structure. The gls function seems not able to recognize the parameters that I pass into the loop function! (But, if I use lm function, it works.) The code looks like this: ================================================= gls.lm <- function(Data, iv1, dv1) { gls.model <- gls(Data[ , dv1] ~ Data[ , iv1], correlation =

Dear Adrian and Ian (and r-helpers), I encountered a curious result in developing an example using the bicreg function in the BMA package: I noticed that pairs of models with equal R^2 and equal numbers of predictors had nevertheless different BIC values. Looking at the bicreg function, the definition of BIC appears to be the usual one, or close to it [bic <- n * log(1 - r2/100) + (size - 1) *

Hi, have two quick questions: I am re-indexing some large mailboxes and I wanted to get some opinions on these speeds. I ran a random sort command on an unindexed mailbox in order to get it to index. Results, for a mailbox with 10GB Inbox, spread in 65 000 files: 3 UID SORT (ARRIVAL) US-ASCII OR OR OR FROM "dfgfgfgf" SUBJECT "dfgfgfgf" TO "dfgfgfgf" CC

* sorry for the other schema, it came out a mess. I hope this one is understandable. hi: I have this 2 boxes set up like this: 2020::2/128 2020::254/128 3030::254/128 192.168.0.2/24 192.168.0.254/24 192.168.30.254/24 +-------+ eth0 eth3 +-------+

Duncan, With the commit from http://lists.cs.uiuc.edu/pipermail/llvm-commits/Week-of-Mon-20121203/158488.html, the Polyhedron 2005 benchmarks complete again on x86_64-apple-darwin12. The result are similar to what were seen with FSF gcc 4.6.2svn and llvm/dragonegg 3.0 (which was the last release that passed pb05) http://lists.cs.uiuc.edu/pipermail/llvmdev/2011-October/044091.html. Jack

Dear all, I wanted to create the mean using a algebra matrix. so I tried this one: > meanAnimals <- new3%*%factorial (Calculates the matrix multiplication of the new3 * factorial). But I get the following error message: Error in new3 %*% factorial : non-conformable arguments These are my matrices: > new3 [,1] [,2] [1,] 1.350 8.1 [2,] 465.000 423.0

Hi there, is there a possibility to count the number of appearances of an element in a vector ? i mean of any given element.. deliver all elements which are exactly xtimes in this vector ? thx in advance !!

Full_Name: Jonathan Lees Version: 2.0.1 OS: linux-gnu Submission from: (NULL) (152.2.75.65) there is a problem with calculating the convex hull in 2-D interpolation using the codes interp fromt eh akima package: x =c(0.6505304, -1.1821562, -0.2600792, 0.7913716) y = c(1.0424226, 0.1754048, -1.4523334, 0.2349112) z = c(0.000, 3.042, 0.370, 0.122) EX = seq(from=min(x), to=max(x),