similar to: GAMs and survival data

How do I construct a figure showing predicted value plots for the dependent variable as a function of each explanatory variable (separately) using the results of a logistic regression? It would also be helpful to know how to show uncertainty in the prediction (95% CI or SE). Thanks- This email has been processed by SmoothZap - www.smoothwall.net

Hi. I am getting an "unexpected symbol" error, which I haven't gotten before. I have checked my data and searched the FAQ. I hoping someone has a suggestion on what I might be doing wrong? Thanks! A. Gray Fisheries Consultant Here's the code I'm using and the error: > 0708smolts <- read.csv("C:\Documents and Settings\ayesha\My

Hi, I use samba 3.0.26a on fedora 8 as a fileserver for a win 2k3 domain. This has worked fine for about 2 months without any problems. However I came to the server 3 days ago and the harddrive was 100% full. On checking I found 60gb of core dumps in the winbind folder. I did a lot of searching and couldnt find anything relevent for this release. I tried upgrading samba to 3.0.28 (fc8

In my daily development, I migrate back and forth between versions, and often do: rake load_fixtures... ... in order to populate my development database with fun data. Now, with any HABTM relationship, there are failures, as there is no way to say "which" fixtures to load first. Within an actual functional or unit test case, you could simply load them in the proper order, but

I have 5 GAMs ( model1, model2, model3, model4 and model5) Before I use some data X(predictor -January to June data) to form a equation and calculate the expected value of Y (predictand -January to June). After variable selection, GAMs (Model 1)were bulit up! R-square :0.40 NOW, I want to use new X'( predictor -July - December data) and put into Model 1, then get the expected value of Y'

hi! I hope all of you can help me this question for example GAMs: ozonea<-gam(newozone~ pressure+maxtemp+s(avetemp,bs="cr")+s(ratio,bs="cr"),family=gaussian (link=log),groupA,methods=REML) formula(ozonea) newozone ~ pressure + maxtemp + s(avetemp, bs = "cr") + s(ratio,bs = "cr") #formula of gams coef(ozonea) # extract the coefficient of GAMs

Hi I have been searching for goodness-of-fit tests (or lack of fit tests) for GAMs and cannot find anything. My problem is: after fitting a GAM to mortality data (smoothing crude estimated rates of mortality - a process called graduation in the actuarial literature), (1) how to assess the fit of the model with reference to "adherence to data" for the fitted model (I do not think the

Hi all, I wonder if it's possible to include a double interaction in a GAM formula. Example: If I do this: mod=gam(energy~s(size, *by=color, by=sex*, k=5) + temperature, ...) I get the interaction betwen size*color and size*sex. But I need size*color*sex, being size a smoother. I've created a new variable (colorsex) which combines all the level of both color (2 levels) and sex (2

Hi I was wondering if anyone knew how to work out the number of knots that should be applied to each variable when using gams in the mgcv library? Any help or references would be much appreciated. Thanks Kathryn Baldwin

Dear R-Users, I am trying to apply a bootstrap to a GAM in order to calculate the 95% confidence intervals for a smooth curve obtained by the ?plot.gam? function of the mgcv package. Nonetheless, I am getting some difficulties in transposing the results for the graphs. I used the following commands in R, ?mgcv? and ?boot? packages: *> attach(bbvc_11Jul08)* *>

Dear R-Users, I am resending this message just to reminder my question regarding the calculation of a bootstrap confidence intervals for a GAM plot. I am trying to apply a bootstrap to a GAM in order to calculate the 95% confidence intervals for a smooth curve obtained by the ?plot.gam? function of the mgcv package. Nonetheless, I am getting some difficulties in transposing the results for

This is my first time running GAMs in R. My csv file has these column headings: "X" "Y" "Sound" "Atlantic" "Blacktip" "Bonnet" "Bull" "Finetooth" "Lemon" "Scalloped" "Sandbar" "Spinner" "Abundance" "Diversity"

Dear list, I?m wondering if there is something analogous to the TukeyHSD function that could be used for parametric terms in a GAM. I?m using the mgcv package to fit models that have some continuous predictors (modeled as smooth terms) and a single categorical predictor. I would like to do post hoc test on the categorical predictor in the models where it is significant. Any suggestions?

Hi there, I was wondering if by the way the isotropic bivariate function works in the mgcv package, one can use highly correlated coordinates (given the shape of the study area) without worrying about the potential problems of correlation between explanatory variables, i.e., does s(LON, LAT) deal with that by considering their combined effect? Although this sounds more like a statistical

Dear list, I'm interested in fitting a generalized additive model in which some of the covariates are derived quantities and known measurement errors, and I am not sure how to incorporate the uncertainty of these covariates into the model fitting process. Could anyone point me towards relevant examples or documentation? Thanks in advance, Julian Julian M. Burgos Fisheries Acoustics

Dear list, I?m using the ?mgcv? package to fit some GAMs. Some of my covariates are derived quantities and have an associated standard error, so I would like to incorporate this uncertainty into the GAM estimation process. Ideally, during the estimation process less importance would be given to observations whose covariates have high standard errors. The gam() function in the ?mgcv? package

Hi, I am looking at the effects of two explanatory variables on chlorophyll. The data are an annual time-series (so are autocorrelated) and the relationships are non-linear. I want to account for autocorrelation in my model. The model I am trying to use is this: Library(mgcv) gam1 <-gam(Chl~s(wintersecchi)+s(SST),family=gaussian, na.action=na.omit, correlation=corAR1(form =~

I have a data assimilation problem that might be amenable to the use of GAMS, but I am not sure how feasible it is to implement. I was told the R mailing list was a great resource. My observations are spatiotemporal salinity in the San Francisco Bay at a number of instruments over a few days. The thing that I want to fit is the initial condition for a salt transport model at the beginning of this

At office I have been introduced by another company to new, complex energy forecasting models using gams as the basic software. I have been told by the company offering the models that gams is specialised in dealing with huge, hevy-weight linear and non-linear modelling (see an example in http://www.gams.com/modtype/index.htm) and they say it is almost the only option for doing it. I would

Greetings This is a long email. I'm struggling with a data set comprising 2,278 hydroacoustic estimates of fish biomass density made along line transects in two lakes (lakes Michigan and Huron, three years in each lake). The data represent lakewide surveys in each year and each data point represents the estimate for a horizontal interval 1 km in length. I'm interested in comparing