similar to: p-level in packages mgcv and gam

I am working with a non-parametic smoothing operation using a Generalized Additive Model. It is a bivariate data set. I know how to do the smooth, and out comes a nice smooth curve. Now I want to find the value of the smoothed curve for several values of x (the abscissa). This can be done (please correct me if I am wrong) by using the predict.gam function. You feed the predict.gam function a

Hi All, When we run the command : summary ( newmod<-gam(Dlq~ formula,family,,data) ) in R, the output would the effect of smoothness in R. As of now to calculate the probability I am following the below approach: 1) Run the plot of the GAM , interpret the curves 2) Re Run the Regression as a GLM after taking into account the non linear terms in step1 3) Calculate the probability from

Hi, This is probably documented, but I cannot find the right words or expression for a search. My attempts failed. I have a data frame of 3 vectors (x, y and z) and would like to transform this so that I could use persp. Presently I have y-level copies of each x level, and a z value for each x-y pair. I need 2 columns giving the possible levels of x and y, and then a transformation of

Hi, I need further help with my GAMs. Most models I test are very obviously non-linear. Yet, to be on the safe side, I report the significance of the smooth (default output of mgcv's summary.gam) and confirm it deviates significantly from linearity. I do the latter by fitting a second model where the same predictor is entered without the s(), and then use anova.gam to compare the

Hi - I have a series of 9 GAM regressions with about 5 parametric effects and three non-parametric effects in each. What is a good library or command for turning GAM outputs into publication-ready regression tables? I tried apsrtable and the mtable command in memisc but neither seemed to work with the gam output. I'd be okay with two separate tables - one for the parametric effects and

Hi, All, I am a beginner for R. Now I have installed R 2.5.1 in Window environment. After I run a program such as "gam" I would like to display a plot for the object. The following is an example. When I did this, only the last plot was presented on my screen. How can I get a plot before the last plot? I mean if the object has several plots how can I get those? "gam.object <-

Hi, In fitting GAMs to assess environmental preferences, I use the part of the fit where the lower confidence interval is above zero as my criterion for positive association between the environmental variable and species abundance. However I like to plot this on the original scale of species abundance. To do so I extract the fit and SE using predict.gam. Lately I compared more

Greetings R world, I know some version of the this question has been asked before, but i need to save the output of a loop into a data frame to eventually be written to a postgres data base with dbWriteTable. Some background. I have developed classifications models to help identify problem accounts. The logic is this, if the model classifies the record as including variable X and it turns out

Hello all, I wish to extract the terms from an rpart object. Specifically, I would like to be able to know what is the response variable (so I could do some manipulation on it). But in general, such a method for rpart will also need to handle a "." case (see fit2) Here are two simple examples: fit1 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis) fit1$call fit2 <-

Greetings All, I am looking to write a parametrized Rscript that will accept a variable name(that also is the name of the flat file), transform the data into a data frame and preform various modeling on the structure and save the output and plot of the model. In this example i am using a rpart decision tree. The only problem i am having is integrating the parameter into the internal object name

Hi, Can we attach a more descriptive "label" (I may use the wrong terminology, which would explain why I found nothing on the FAQ) to variable names, and later have an easy way to switch to these labels in plots? I fear this is not possible and one must enter this by hand as ylab and xlab when making plots. Thanks in advance, Denis Chabot

Philipp Benner reported a Debian bug report against r-cran-rpart aka rpart. In short, the issue has to do with how rpart evaluates a formula and supporting arguments, in particular 'weights'. A simple contrived example is ----------------------------------------------------------------------------- library(rpart) ## using data from help(rpart), set up simple example myformula <-

I am using the rpart package and seem to have trouble with data sets that have columns with no data. I look at the column data in R and all values are NA. When this occurs, I get nothing back from the rpart function. Is there a way to get the rpart package to ignore these columns, without knowing what columns are empty? I have tried the na.action=na.omit and na.action=na.exclude, but neither one

Hi R-helpers. I have the following problem: I would like to apply my function gain(df,X,A) to a list of arguments. df is a data frame X,A are the varibales od data frame. When I do > gain(kyphosis,"Kyphosis",c("Start","Number")) [1] "Start" "Number" I get the following error... Error in unique.default(x) : unique() applies only to vectors I

Hi, Suppose i have generated an object using the following : fit <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis) And when i print fit, i get the following : n= 81 node), split, n, loss, yval, (yprob) * denotes terminal node 1) root 81 17 absent (0.7901235 0.2098765) 2) Start>=8.5 62 6 absent (0.9032258 0.0967742) 4) Start>=14.5 29 0 absent (1.0000000

I run the following code: library(rpart) data(kyphosis) fit <- rpart(Kyphosis ~ ., data=kyphosis) plot(fit) text(fit, use.n=TRUE) The text labels represent the count of each class at the leaf node. Unfortunately, the numbers are rounded and in scientific notation rather than the exact number of examples sorted by that node in each class. The plot is supposed to look like

Hi, I'm wondering why 48 %/% 2 gives 24 but 4.8 %/% 0.2 gives 23... I'm not trying to round up here, but to find out how many times something fits into something else, and the answer should have been the same for both examples, no? On a different topic, I like the behavior of NAs better in R than in SAS (at least they are not considered the smallest value for a variable), but at the

Dear R-users I am using RPART package to get regression trees. However having trouble getting the text function to put the full splitting rule number on the plot, instead to puts it in scientific notation. When a covariate has 1e4 or greater number of digits then the splitting rule number displayed on the plot is in scientific notation. But print.rpart displays the splitting rules in full.

Hi, As part of the legend to a plot, I need to have the "n" in italics because it is a requirement of the journal I aim to publish in: "This study, n = 3293" Presently I have: legend(20, 105, "This study, n = 3293", pch=1, col=rgb(0,0,0,0.5), pt.cex=0.3, cex=0.8, bty="n") I suppose I could leave a blank in place of the "n",

Hi, I have read about the use of symbols() to draw circles of different sizes, but I have not been able to find out how to add a legend to such a graph, legend that would display some specific sizes and their meaning. Before finding the symbols function in Paul Murrell's book, I had rolled by own function where the variable I want to use to control circle size was actually used to