similar to: help with GAM

Dear R users, I have a question about the plot with the package gam. I need to plot different main effect functions, related to different gam models, in the same graphics (i.e. the same covariate about different models). I used the plot.gam e preplot.gam documentations. Using preplot.gam I can plot the single function but I'm not able to put all the functions together. Does anybody can help

Dear R users, I'm new to both R and to this list and would like to get advice on how to build generalized additive models in R. Based on the description of gam, which I found on the R website, I specified the following model: model1<-gam(ST~s(MOWST1),family=binomial,data=strikes.S), in which ST is my binary response variable and MOWST1 is a categorical independent variable. I get the

I am trying to get the function "Models" to work each time there is an instance of k. This code will stop after the first model is complete. I need it to come back and pass the next value of c into the "Initial.State" function. any ideas? col<-c(23:28) #Setup for(k in col){ Initial.State(Response=zample[,c(k,29)], Explanatory=zample[,variable_columns],

Hello fellow R's, I do apologize if this is a basic question. I'm doing some GAMs using the mgcv package, and I am wondering what is the most appropriate way to determine how much of the variability in the dependent variable is explained by each term in the model. The information provided by summary.gam() relates to the significance of each term (F, p-value) and to the

In Dr. Wood's book on GAM, he suggests in section 4.1.6 that it might be useful to shrink a single smooth by adding S=S+epsilon*I to the penalty matrix S. The context was the need to be able to shrink the term to zero if appropriate. I'd like to do this in order to shrink the coefficients towards zero (irrespective of the penalty for "wiggliness") - but not necessarily all the

Hi, I hope somebody can help me with this issue: I am doing population pyramids using the barplot command, so in the left side I have male age structure and in the right side the female age structure. To plot the male age structure I put the data in negative numbers. Now, I want to change the sign in the bar plot in such way that I have no-sign numbers, both in left and right side of the graph. I

Hi, I am fitting two models, a generalized linear model and a generalized additive model, to the same data. The R-Help tells that "A generalized additive model (GAM) is a generalized linear model (GLM) in which the linear predictor is given by a user specified sum of smooth functions of the covariates plus a conventional parametric component of the linear predictor." I am fitting the GAM

I have a matrix containing means and CIs (lower and upper in two columns, so three columns for every data point) for several points. I have to build a graph of these means accompained by the CIs (as wiskers). No problems with making the graph of means, but I don't know how to introduce CIs. Can anybody advise? -- View this message in context:

Hello, I'm new to R, and I would like to know if there is a way to smooth a curve using a Gaussian smoothing with R. Thank you very much, TDB -- View this message in context: http://www.nabble.com/Gaussian-Smoothing-tp14321313p14321313.html Sent from the R help mailing list archive at Nabble.com.

Hello, I'm trying to do cor(x1,x2) and I get the following error: Error in cor.default(x1, x2) : missing observations in cov/cor A few things: 1. I've used cor() many times and have never encountered this error. 2. length(x1) = length(x2) 3. is.numeric(x1) = is.numeric(x2) = TRUE 4. which(is.na(x1)) = which(is.na(x2)) = integer(0) {the same goes for is.nan()} 5. I also try

Dear List, I'm using GAMs in a multiple imputation project, and I want to be able to combine the parameter estimates and covariance matrices from each completed dataset's fitted model in the end. In order to do this, I need the knots to be uniform for each model with partially-imputed data. I want to specify these knots based on the quantiles of the unique values of the non-missing

Hi, all I want to choose same knots in GAM for 10 different studies so that they has the same basis function. Even though I choose same knots and same dimensions of basis smoothing, the basis representations are still not same. My command is as follows: data.gam<-gam(y~s(age,bs='cr',k=10)+male,family=binomial,knots=list(age=seq(45,64,length=10))) What is my mistake for choice of

The myoglobin sequence, with reference number NM_005368 in Gen bank, has the following frequencies of DNA nucleotides: A C G T 237 278 309 242 Do these data provide sufficient evidence, at the 1% level of significance, that the DNA nucleotides have an unequal distribution, that is the DNA nucleotides are not evenly utilised? Clearly state your hypothesis, test statistic and conclusion.

Hi, the standard errors of the coefficients in two regressions that I computed by hand and using lm() differ by about 1%. Can somebody help me to identify the source of this difference? The coefficient estimates are the same, but the standard errors differ. ####Simulate data happiness=0 income=0 gender=(rep(c(0,1,1,0),25)) for(i in 1:100){ happiness[i]=1000+i+rnorm(1,0,40)

Hi all, I am using GAM to model time trends in a logistic regression. Yet I would like to extract the the fitted spline from it to add it to another model, that cannot be fitted in GAM or GAMM. Thus I have 2 questions: 1) How can I fit a smoother over time so that I force one knot to be at a particular location while letting the model to find the other knots? 2) how can I extract the matrix

Hi So my particular problem is this: I have a row vector of length 5200 elements - specifically created by x<-rbinom(5200,1,0.5) y<-matrix(x,nrow=1,ncol=5200) y now, each element is either a 0 or a 1 - e.g. it could be (0,1,1,1,1,0,0,0,1,1,1) e.t.c. when the element is a 1, i need to multiply a number (say 1000) by 1.005, and if it is 1 again, multiply it _again_ by 1.005. so for

I am writing a rd doc, and need to use "#" in a url adress. This would make: \url{http://www.xxxx.org/myfolder/#myanchor} Of course, I suppose this will not work because # is a special character starting a comment line in the rd dialect. I did not found a similar example in "Writing R exentions". I am not sure bout using \dQuote{a quotation}), and use \sQuote and \dQuote

Hi, there, I have 5 datasets. I would like to choose a basis spline with same knots in GAM function in order to obtain same basis function for 5 datasets. Moreover, the basis spline is used to for an interaction of two covarites. I used "cr" in one covariate, but it can only smooth w.r.t 1 covariate. Can anyone give me some suggestion about how to choose a proper smoothing spline

I would like to fit a logistic regression using a smothing spline, where the spline is a piecewise cubic polynomial. Is the knots option used to define the subintervals for each piece of the cubic spline? If yes and there are k knots, then why does the coefficients field in the returned object from gam only list k coefficients? Shouldn't there be 4k -4 coefficients? Sincerely, Bill

Hi all, I'm trying to use a gam (mgcv package) to analyse some data with a roughly U shaped curve. My model is very simple with just one explanatory variable: m1<-gam(CoT~s(incline)) However I just keep getting the error message "Error in smooth.construct.tp.smooth.spec(object, dk$data, dk$knots) : A term has fewer unique covariate combinations than specified maximum degrees of