similar to: Use estimated non-parametric model for sensitivity analysis

Hi, I would appreciate if someone could help me on track with this problem. I want to compute some parameters from a system of equations given a number of sample observations. The system looks like this: sum_i( A+b_i>0 & A+b_i>C+d_i) = x sum_i( C+d_i>0 & C+d_i>A+b_i) = y sum_i( exp(E+f_i) * ( A+b_i>0 & A+b_i>C+d_i) = z A, C, E are free variables while the other

Dear All, Apologies if this is too simple for this list. Let us assume that you have an instrument measuring particle distributions. The output is a set of counts {n_i} corresponding to a set of average sizes {d_i}. The set of {d_i} ranges from d_i_min to d_i_max either linearly of logarithmically. There is no access to further detailed information about the distribution of the measured sizes, but

Hi, all, Does anyone know how to get the functional form of the smooth terms in GAM? eg. I fit y=a+b*s(x) where s is the smooth function. After fitting this model with GAM in R, I want to know the form of the s(x). Any suggestion is appreciated. Thanks, Jin --------------------------------- Ahhh...imagining that irresistible "new car" smell?

Hi all, I am doing some experiment studies... It seems to me that with different combination of 5 parameters, the end results ultimately converged to two scalars. That's to say, some combinations of the 5 parameters lead to one end result and some other combinations of the 5 parameters lead to the other end result (scalar). I am thinking of this is sort of something like clustering or

This is in regards to the suggested use of type="lpmatrix" in the documentation for mgcv::predict.gam. Could one not get the same result more simply by using type="terms" and interpolating each term directly? What is the advantage of the lpmatrix approach for prediction outside R? Thanks. -- View this message in context:

Dear R-Users, Dr. Wood replied to a similar topic before where confidence intervals were for a ratio of two treatments ( https://stat.ethz.ch/pipermail/r-help/2011-June/282190.html). But my question is more complicated than that one. In my case, log(E(y)) = s(x) where y is a smooth function of x. What I want is the confidence interval of a ratio of log[(E(y2))/E(y1)] given two fixed x values of

Dear Simon, Thank you for your quick reply! I used to perform the GAMsetup in the following manner: GAMsetup sintax: x.summer: vector used for construct the spline knots<-14 N<-length(x.summer) x<-array(x.summer,dim=c(1,N)) G<-list(m=1,n=N,nsdf=0,df=knots+1,dim=1,s.type=0,by=0,by.exists=FALSE,p.order=0,x=x,n.knots=knots,fit.method="mgcv") H<-GAMsetup(G) with the

Hi folks, I originally tried R-SIG-Mixed-Models for this one (https://stat.ethz.ch/pipermail/r-sig-mixed-models/2010q3/004170.html), but I think that the final steps to a solution aren't mixed-model specific, so I thought I'd ask my final questions here. I used gamm4 to fit a generalized additive mixed model to data from a AxBxC design, where A is a random effect (human participants in

R-help, Sorry for posting again the same question (dated 26-03-2007) but all my mails have been sent to the recycle bin without possibility of recovering and thus I don't know if anyone has answer my query. Here is the original message: I'm applying a gam model (package mgcv) to predict relative abundances of a fish species. The covariates are year, month, vessel and statistical

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 I'm puzzled as to the relation between the REML score computed by gam and the formula (4) on p.4 here: http://opus.bath.ac.uk/22707/1/Wood_JRSSB_2011_73_1_3.pdf I'm ok with this for poisson, or for quasipoisson when phi=1. However, when phi differs from 1, I'm stuck. #simulate some data library(mgcv) set.seed(1) x1<-runif(500) x2<-rnorm(500)

Hi, I was wondering if there is a function in R which performs bivariate non parametric smoothing which allows for the possibility of including some weights in the smoothing (for each data points in my grid I have some predefined weights that I would like to include in the smoothing). Thanks, Ben _________________________________________________________________ [[alternative HTML

Sorry if this is an obvious question... I'm estimating a simple binomial generalized additive model using the gam function in the package mgcv. The model makes sense given my data, and the predicted values also make sense given what I know about the data. However, I'm having trouble interpreting the y-axis of the plot of the gam object. The y-axis is labeled "s(x,2.52)"

Hello, Is it possible to estimate prediction interval using GAM? I looked through ?gam, ?predict.gam etc and the mgcv.pdf Simon Wood. I found it can calculate confidence interval but not clear if I can get it to calculate prediction interval. I read "Inference for GAMs is difficult and somewhat contentious." in Kuhnert and Venable An Introduction to R, and wondering why and if that

Hi! I'm learning mgcv, and reading Simon Wood's book on GAMs, as recommended to me earlier by some folks on this list. I've run into a question to which I can't find the answer in his book, so I'm hoping somebody here knows. My outcome variable is binary, so I'm doing a binomial fit with gam(). I have five independent variables, all continuous, all uniformly

Dear all, When using GAM function in R, we need to specify the degree of freedom for the smooth function (i.e. s=(x, df=#)). I am wondering how to choose an appropriate df. Thanks a lot, Jin ---- North Carolina State University USA --------------------------------- [[alternative HTML version deleted]]

Hi, This is Chandra. I have Polycom IP 501 phone. Its showing wrong time on the display screen. How can I set the "New York" time? What value I have to give to GMT offset value? Look forward to your response. Thank you. Regards, Chandra. --------------------------------- Ahhh...imagining that irresistible "new car" smell? Check outnew cars at Yahoo! Autos.

Hi, I have configured the below things: Extensions Trunk Outbound route Inbound route IVR Ring group If anybody call to my DID number, my IVR is responded. After that, if he press 1, then Ring group will be activated. All are working fine. My Problem: I want to avoid IVR for some phone numbers depends on their called IDs. If my common users will call to my DID

Where is the code that maps the kernel of a DomU into memory? i.e, when you do a xm create <config file> what code is called to actually map the kernel into memory? Is it a python script or is it re-directed to Dom0 to do? Thanks. -Brian --------------------------------- Ahhh...imagining that irresistible "new car" smell? Check outnew cars at Yahoo! Autos.

Where is the code that maps the kernel of a DomU into memory? i.e, when you do a xm create <config file> what code is called to actually map the kernel into memory? Is it a python script or is it re-directed to Dom0 to do? Thanks. -Brian --------------------------------- Ahhh...imagining that irresistible "new car" smell? Check outnew cars at Yahoo! Autos.