search for: pointwise

Hi all. I hope I have my terminology right here... For a simple lm, one can add ?pointwise confidence bounds? to a fitted line using something like >predict(results.lm, newdata = something, interval = "confidence") (I'm following DAAG page 154-155 for this) I would like to do the same thing for a glm of the logistic regression type, for instance, the example in MASS p...

Dear all, Is there a way to plot / calculate pointwise confidence bands or interval values for a non parametric regression like sm.regression? Thank you in advance. Regards, Martin

...m prices, and do something like: returns.z = tail(prices.z,-1)/head(prices.z,-1) - 1 # should be equivalent to returns = exp(diff(log(prices.z))) - 1 Curiously, I get a zoo object back with zeros everywhere and also with the index having one fewer element than it should. Does anyone know how to pointwise divide zoo objects, and what exactly "/" is doing? [[alternative HTML version deleted]]

...atement that can be attached to these connected confidence/prediction intervals, this does not seem reasonable to me. This is done, for example, in ISWR pg. 105, UsingR for Introductory Statistics pg 296, and Linear Models with R pg. 39 (Although in this instance the intervals are called 95% "pointwise" confidence bands versus simply 95% confidence bands.) To make a confidence/prediction band, one should construct simultaneous confidence/prediction intervals with say a Scheffe approach as mentioned in the S-PLUS Guide to statistics pg 274. If these connected intervals were called pointwis...

...ot.Result=matrix(nrow=B,ncol=n) for ( b in 1:B){  Data.Orig.Boot=PairedBootstrap(Data.Orig)       fit.Boot=predict(fit,newdata=Data.Orig.Boot,type="response")  Boot.Result[b,]=fit.Boot  }   And try to find 95% confidence interval for 1000 copies of y corresponding to each x. ConfidenceSet.Pointwise=function(Boot.Result,alpha){   n=ncol(Boot.Result)   B=nrow(Boot.Result)   SetBounds=matrix(ncol=2,nrow=n)   for(j in 1:n){             Result.Sort=sort(Boot.Result[,j])   SetBounds[j,1]=Result.Sort[floor(0.5*B*alpha)]        SetBounds[j,2]=Result.Sort[ceiling(B*(1-0.5*alpha))]   }   return(SetBoun...

...son intervals for binomial data at each time) or when there is progressive type II censoring. Simulations show at least nominal coverage for independent censoring. Also, it is fast so it can be used routinely. For a complete description of the new method see Fay, Brittain, and Proschan (2013). Pointwise confidence intervals for a survival distribution with small samples or heavy censoring. Biostatistics doi:10.1093/biostatistics/kxt016 (available at http://www.niaid.nih.gov/about/organization/dcr/brb/staff/Pages/michael.aspx ). Mike **************************************************************...

...r = 1, vec = u, mat = A, val = 4) I would like to integrate a function ("integrand") which gets an "x" value (the running variable), a vector ("vec"), a matrix ("mat"), and a value ("val"). This function returns a number (set to 1 here). Of course, pointwise evaluation works without flaws. But why does integration not work? I obtain: Error in integrate(integrand, lower = 0, upper = 1, vec = u, mat = A, : evaluation of function gave a result of wrong length Cheers, Marius

Hi All, I am running a scatter plot and trying to add a best fit line. I use an abline function, but get no line drawn over the points. I also get no error. I arm using V 2.10.0 on Windows 7. Here is my code, including the SAS transport file import: require (foreign) require (chron) require (Hmisc) require (lattice) clin <- sasxport.get("y:\\temp\\subset.xpt") attach(clin)

...implemented in S-plus (and may be OK for truly nested models). And even if it's been decided that this functionality is not wanted in mgcv, perhaps another function comparing several models by the GCV/UBRE score and other useful statistics can be implemented? 3. Some authors [1, 2] suggests pointwise estimation of odds ratios and corresponding confidence intervals based on the smooth terms in a GAM. Maybe something for mgcv? [1] Figueiras, A. & Cadarso-Su?rez C. (2001) "Application of Nonparametric Models for calculating Odds Ratios and Their Confidence Intervals for Continuous Exp...

Hello list, i'm going to try very hard not to rant here, but i've been trying to get Samba working for 3 days, and it's just not happening. Let me start from the beginning. i'm just a lowly Windows admin but i've been doing this for 10 years, so i'm pretty sure i know what i'm doing (present situation excepted, clearly). i've got RedHat AS4 and a primarily

...y be a no brainer, but I could not find pointers to efficient computation of this beast in past help files. Background - I wish to implement a Cramer-von Mises type test statistic which involves double sums of max(X_i,Y_j) where X and Y are vectors of differing length. I am currently using ifelse pointwise in a vector, but have a nagging suspicion that there is a more efficient way to do this. Basically, I require three sums: sum1: \sum_i\sum_j max(X_i,X_j) sum2: \sum_i\sum_j max(Y_i,Y_j) sum3: \sum_i\sum_j max(X_i,Y_j) Here is my current implementation - any pointers to more efficient computation...

Dear all, Is there any package or function can do the pointwise confidence interval and confidence band for the local polynomial regression? Maybe the local linear regression is enough. Thanks. Regards, Zhen

Hello, Is there any other bivariate pointwise interpolation command besides akima's interpp? I tried to search through the J. Baron's page without luck. The problem is that I have got regularly spaced data (in x and y) what is not acceptable for interpp. I am not very much interested in the method of interpolation as the data are...

...ing loess function. My problem is that when I have a loess object I don't know how to display the fitted surface; in fact, while in S when you have a loess object you can see it writing plot(object), in R this dosen't work. Also I'd like to know if there is something like the S function pointwise that computes upper and lower confidence intervals. Thank you very much for your attention. Marta Colombo

...xample, I get the folling error message: example(cobs) cobs> x <- seq(-1, 3, , 150) cobs> y <- (f.true <- pnorm(2 * x)) + rnorm(150)/10 cobs> con <- rbind(c(1, min(x), 0), c(-1, max(x), 1), c(0, 0, 0.5)) cobs> Rbs <- cobs(x, y, constraint = "increase", pointwise = con) qbsks2(): Performing general knot selection ... Error in as.matrix.csr(new("matrix.coo", ra = c(z1$design), ia = i1, ja = j1, : unable to find a non-generic version of function "as.matrix.csr" Any suggestions how to fix this problem? Thank you for your help....

I would like to apply a function 'f' to the lagged version of a vector and the vector itself. This is easy to do explicitly: mapply( f, v[-1], v[-length(v)] ) or in the case of a pointwise vector function, simply f( v[-1], v[-length(v)] ) This is essentially the same as 'diff' but with an arbitrary function, not '-'. Is there a standard way to do this? Is there any particular reason that 'diff' should not have an 'f' argument? -s...

...k = 0700 #printable = no csc policy = disable #force user = %U [homes] comment = Home Directories read only = No guest ok = No browseable = No map read only = Permissions directory mask = 0755 [printers] comment = All Printers path = /usr/spool/samba printable = Yes browseable = No [Pointwise] comment = Pointwise Corporate Files path = /opt/domain #create mask = 0765 force create mode = 664 force group = pwi browseable = Yes printable = No guest ok = No writeable = Yes read only = No [Backups] comment = Backup files are stored here path = /opt/backups browseable = Yes pri...

Dear R users, The package 'mfp' that fits fractional polynomial terms to predictors. Example: data(GBSG) f <- mfp(Surv(rfst, cens) ~ fp(age, df = 4, select = 0.05) + fp(prm, df = 4, select = 0.05), family = cox, data = GBSG) print(f) To describe the association between the original predictor, eg. age and risk for different values of age I can plot it the polynomials

Dear R-users, I have tried, and I imagine it should be somewhere in the lines of passing extra arguments to the panel function, but does anyone know how to change the character expansion factor that is affecting an individual point in each of the panels of a lattice plot? I have tried to pass an overall cex argument containing the desired size for each point, but then the sizes are reused for the

Hello everybody-- I have been playing with my data in spatstat, and what I'd like to present is a basic exploratory spatial analysis. I have used the following code, using a ppp.object called tsdspoints. The code develops the simulations and the envelopes I want, but I don't understand my first plot here, the [tsds.ghat.short$r, tsds.ghat.short$raw]...I cobbled together this code