similar to: compare GLM coefficients

Many thanks for taking the time to read this! I am looking at the repeatability of behaviour between re-sighted individuals across discrete time periods (annual breeding seasons). My approach was to run a GLM (with a logit link - the data are proportional, presence v. absence of behaviour) for each breeding season. I included the re-sighted individuals as a factor (categorical variable) (i.e.

Hi i am doing an environmental research The equation is as follow: gam(y1 ~ x1 + s(x2) + s(x3) + s(x4), family = gaussian, fit = true) I would like to obtain the beta coefficient and 95CI of x4 (or s(x4)), what should I do? Thanks, Lung -- View this message in context: http://r.789695.n4.nabble.com/mgcv-beta-coefficient-and-95-CI-tp3320491p3320491.html Sent from the R help mailing list

Hello I'm analyzing a dichotomous dependent variable (dv) with more than 100 measurements (within-subjects variable: hours24) per subject and more than 100 subjects. The high number of measurements allows me to model more complex temporal trends. I would like to compare different models using GLM, GLMM, GAM and GAMM, basically do demonstrate the added value of GAMs/GAMMs relative to

I am trying to understand my population abundance data and am looking into analyses of change point to try and determine, at approximately what point do populations begin to change (either decline or increasing). Can anyone offer suggestions on ways to go about this? I have looked into bcp and strucchange packages but am not completely convinced that these are appropriate for my data. Here is

Dear R-list, I have a statistical problem with the comparison of short time-series, representing densities of fish in different streams. For each stream (6 in total, here below showed only part of the dataset) I have 8 years of density data, as follows: year density stream 1 2000 0.51 stream1 2 2001 0.87 stream1 3 2002 0.68 stream1 4 2003 0.56 stream1 5 2004 0.50 stream1 6

Hi, I am using mgcv:gam and have developed a model with 5 smoothed predictors and one factor. gam1 <- gam(log.sp~ s(Spr.precip,bs="ts") + s(Win.precip,bs="ts") + s( Spr.Tmin,bs="ts") + s(P.sum.Tmin,bs="ts") + s( Win.Tmax,bs="ts") +factor(site),data=dat3) The total deviance explained = 70.4%. I would like to extract the variance explained

Hello, I am a new R user and I am trying to estimate some generalized linear models (glm). I am trying to compare a model with a gaussian distribution and an identity link function, and a poisson model with a log link function. My problem is that while the gaussian model has significantly lower (i.e. "better") AIC (Akaike Information Criterion) most of the coefficients are not

I am using a binomial mixture model to estimate abundance (N) and detection probability (p) using simulated count data: -Each site has a simulated abundance that follow a Poisson distribution with lambda = 5 -There are 200 simulated sampled sites -3 repeated counts at each site - only 50 percent of the animals are counted during each count (i.e, detection probability p =0.5, see codes) We removed

Initially reported to debian (http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=810964), redirected here: With AMD Opteron 6xxx processors, half of the memory controllers are missing from /sys/devices/system/edac/mc Checked with single 6120 (dual memory controller) and twin 6344 (2x dual MC), other dual-module CPUs might be affected too. Booting plain Linux (3.2, 3.16, 4.1, 4.3), all memory

Apologies for the empty email earlier! I have species abundance data sampled at a weekly frequency or sometimes monthly depending on the year. The goal is to identify the dates in an annual cycle in which the cumulative abundance of a species reaches some threshold. Here's an example of the data for 1 species over an annual period: "mc_pheno" is the object created from this data:

At my physics lab we have 30 servers with 1TB disk packs. I am in need of monitoring for disk failures. I have been reading about SMART and it seems it can help. However, I am not sure what to look for if a drive is about to fail. Any thoughts about this? Is anyone using this method to predetermine disk failures? TIA

I am a graduate student who's just starting to use more advanced statistics and is completely new to R. ?I'm looking for whether parasite prevalence varies with region. ?I'd like to try using just a subset of the data defined by one these covariates, sex, looking at data only from adults, without using it as a covariate in the analyses. ?I tried using subset=sex=='A' in the

Env: R 2.8.1, Win Xp, Eclipse/StatET In a .Rd file, I have an example containing the lines: # calculate Y M, using polynomial contrasts trends <- as.matrix(VocabGrowth) %*% poly(8:11, degree=3) colnames(trends)<- c("Linear", "Quad", "Cubic") [At the risk of a long message, I'll append the complete .Rd file at the end of this message, in case this was

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Hi!, I'm really hoping someone out there will be able to help me. I recently started my MSc dissertation on Population Projection Matrices, which has been going well until now. I am trying to set-up a general script that does a pairwise comparison of all elements in my matrices. So for example, given that I have the following matrix S: > S [,1] [,2] [,3] [1,]

Hi, Out of curiosity, has anyone managed to use mail-trends[0] to analyse their e-mails. I thought about trying it out, but got stuck midstream. The mail-trends scripts work very well with gmail, but because they say it is supposed to work with _any_ IMAP server, I thought I could get it running with Dovecot too. I know this is NOT a mail-trends support group though, but I believe there is

Hello, I have a model glm(Y ~ X, family = quasipoisson(link = "identity")) I would like to vary the coefficient for X and observe the effect on the deviance. Is this possible? Many thanks, Dan Bebber Department of Plant Sciences University of Oxford

Dear list members, I was reminded of what I see as a problem with summary.glm this week when some of my students fell into a trap in a homework exercise, defining a logit model in which coefficients were aliased. When this happens in lm, summary.lm prints a message ["Coefficients: (1 not defined because of singularities)"], but summary.glm is silent. In both instances, the print

Hi and sorry to distur, ########### Setting ################# I'm trying to use glm with factors: > Pyr.1.glm<-glm(Pyrale~Trait,DataRav,family=poisson) > summary(Pyr.1.glm) Call: glm(formula = Pyrale ~ Trait, family = poisson, data = DataRav) Deviance Residuals: Min 1Q Median 3Q Max -1.7117 -0.8944 -0.6237 0.6390 1.5224 Coefficients: Estimate Std. Error z value Pr(>|z|)

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