similar to: GAMs with errors in covariates

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

Hello fellow R's, I'm sure there must be an easy way to do this. But after digging in the documentation and thinking about it for a while I couldn't figure it out. I need to get a decreasing recursive vector in. I mean something like this: if starting at 2, and ending at 6, the vector should be 2 3 4 5 6 3 4 5 6 4 5 6 5 6 6 An easy way would be to do this x <-

Dear list, I do apologize if these are basic questions. I am fitting some GAM models using the mgcv package and following the model selection criteria proposed by Wood and Augustin (2002, Ecol. Model. 157, p. 157-177). One criterion to decide if a term should be dropped from a model is if the estimated degrees of freedom (EDF) for the term are close to their lower limit. What would be the

Hello R list, I need to compute empirical variograms using data from a large geographic area (~10^6 km2). Although I could not find a specific reference, I assume that both geoR and gstat calculate distances among data points assuming points are on a flat surface (using the Pythagorean Theorem). Because the location of my data is large and located near the pole, assuming that latitude and

Hello fellow R's, I apologize if this question was answer elsewhere. I have an executable file that I need to run from R. Basically I want to use R to create the input files this executable requires, then run it, and finally use R again to analyze the output files. Because I have to do this many times I'd like to have the R code call the executable file after the input files are

Dear all, I am a new user of R. I would like to know how to get fund's returns in percentage (%). For example, I use: R <- ts(read.xls("FundData"), frequency = 12, start = c(1996, 1)) Whith this program, the returns are like 0.0152699. But, I would like to have 1.52%. Please advise me about the function. Thanks! Fabrice

Hi All, I have a data.frame: >pop consumed ind recruits gonad cell 1 516.74 1 0.02 20.21 0.25 2 1143.20 1 0.02 20.21 0.50 3 250.00 1 0.02 20.21 0.25 4 251.98 1 0.02 18.69 0.25 5 598.08 1 0.02 18.69 0.25 6 437.38 1 0.02 18.69 0.25 7 250.00 1 0.02 17.39 0.25 8 250.00 1 0.02 17.39 0.25 9

Dear list, Hello! I have a question about how to print a label in the plot. I am using the following code: <pdf("mel4_chr3_11cancer_cghFLasso.pdf", height=6, width=5);plot(Disease.FL, index=i, type="Single",main="Plot of Labels");dev.off(); But "Plot of Labels" has not been printed. Any suggestions? Thanks a lot! Allen

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?

What is the name of the function to give me the mode (central tendancy) of a numeric variable that can be negative? [[alternative HTML version deleted]]

I am using gam in mgcv (1.3-22) and trying to use gcv to help with model selection. However, I'm a little confused by the process of assessing GCV scores based on their magnitude (or on relative changes in magnitude). Differences in GCV scores often seem "obvious" with my poisson gams but with negative binomial, the decision seems less clear. My data represent a similar pattern as

Dear list, Could someone show me where can I find the detailed formula on how to calculate the two way anova with unbalanced design? Say, if I have 2*2 design with 10,20,30,40 samples in each of the 2*2 cells. Most of the places I've googled only show how to calculate using software such as R, but not clear the detailed formula for calculating this. Thanks, Jack [[alternative HTML version

Hi All, I am new in R and trying to simulate random normal 2D field with mean trend say north-south. My domain is 10x10 grid and I am trying to use mvnorm but do not know how to specify the domain and the mean field. I would appreciate any help. Cheers, SK --------------------------------- [[alternative HTML version deleted]]

Hi. I am plotting graphs for values ranging between -1 and 10, for example: (1,2,1,1,6,7,-1,-1,5,-1) I am trying to plot the graphs so that the points with value of -1 will be in one specific color, and the rest of the points will be in one different specific color. I would be grateful for any idea of how to do that in two colors. Thanks for any hint. -- View this message in context:

Hi All, I am busy using R to do some regression modelling and have been using plot(x,y,"") to visualise my variables. I would now like to label my points using data stored in the data.frame used for the regression analysis. For example each of my data points is made up of a field measured forest volume value and a remotely sensed vegetation estimate (NDVI). Each point is an enumeration

I'm interested in writing a function that constructs a new plot on the current graphics device if no plot exists there yet, but adds lines to the existing plot if a plot is already there. How can I do this? It seems to me that the exists() function might be co-opted to do this, but it's not obvious how. Many thanks, Roger -- Roger Levy Email: rlevy at ucsd.edu

Hi I am working on R 2.5.0 on window. I am trying to provide a Hyper-link to the user as a result, I have tried using gtkLinkButton to exercise the facility, however, i am not able to perform the required task, i.e. when I clicked on the LinkButton actually nothing happened. I have gone through the documentation for the same and found that GtkLinkButtonUriFunc is a function which is require to

Dear list, I´m using the mgcv package to model the proportion by weight of certain prey on the stomach content of a predator. This proportion is the ratio of two weights (prey weight over stomach weight), and ranges between 0 and 1. The variance is low when proportion is close to 0 and 1, and higher at intermediate values. It seems that the best way to go is to model this using the

Picking up an ancient thread (from Oct 2007), I have a somewhat more complex problem than given in Simon Wood's example below. My full model has more than two smooths as well as factor variables as in this simplified example: b <- gam(y~fv1+s(x1)+s(x2)+s(x3)) Judging from Simon's example, my guess is to fit reduced models to get components of deviance as follows: b1 <-

Dear list, I´m calculating time differences between series of time stamps and I noticed something odd: If I do this... > time1=strptime("2009 05 31 22 57 00",format="%Y %m %d %H %M") > time2=strptime("2009 05 31 23 07 00",format="%Y %m %d %H %M") > > diff(c(time1,time2),units="mins") Time difference of 10 mins .. I get the correct