similar to: Return function from function and Recall()

Hi, forget about the below details. It is not related to the fact that the function is returned from a function. Sorry about that. I've been troubleshooting soo much I've been shoting over the target. Here is a much smaller reproducible example: x <- 1:10 y <- 1:10 + rnorm(length(x)) sp <- smooth.spline(x=x, y=y) ypred <- predict(sp$fit, x) # [1] 2.325181 2.756166 ...

Here I think S3 dispatch is very natural. Try the following: page <- function(x, method = c("dput", "print"), ...) UseMethod("page") page.getAnywhere <- function(x, ..., idx=NULL) { name <- x$name; objects <- x$obj; if (length(objects) == 0) stop("no object named '", name, "' was found"); if (is.null(idx)) {

Hello, Right! I copied from the OP's question without thinking about it. Corrected would be bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d$crp median((y - ypred)^2) } Sorry, rui Barradas On 5/22/2018 11:32 AM, Daniel Nordlund wrote: > On 5/22/2018

Dear R-help, I have fitted a glm logistic function to dichotomous forced choices responses varying according to time interval between two stimulus. x values are time separation in miliseconds, and the y values are proportion responses for one of the stimulus. Now I am trying to extrapolate x values for the y value (proportion) at .25, .5, and .75. I have tried several predict parameters, and they

I forgot, you should also set.seed() before calling boot() to make the results reproducible. Rui Barradas On 5/22/2018 10:00 AM, Rui Barradas wrote: > Hello, > > If you want to bootstrap a statistic, I suggest you use base package boot. > You would need the data in a data.frame, see how you could do it. > > > library(boot) > > bootMedianSE <- function(data,

Hi, this relates to the question "How to set a former environment?" asked yesterday. What is the best way to to return a function with a minimal environment from a function? Here is a dummy example: foo <- function(huge) { scale <- mean(huge) function(x) { scale * x } } fcn <- foo(1:10e5) The problem with this approach is that the environment of 'fcn' does not

Hi, I am trying to integrate a function which is approximately constant over the range of the integration. The function is as follows: > my.fcn = function(mu){ + m = 1000 + z = 0 + z.mse = 0 + for(i in 1:m){ + z[i] = rnorm(1, mu, 1) + z.mse = z.mse + (z[i] - mu)^2 + } + return(z.mse/m) + } > my.fcn(-10) [1] 1.021711 > my.fcn(10) [1] 0.9995235 > my.fcn(-5) [1] 1.012727 > my.fcn(5)

Hello, If you want to bootstrap a statistic, I suggest you use base package boot. You would need the data in a data.frame, see how you could do it. library(boot) bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d$crp median(y - ypred)^2 } dat <-

On 5/22/2018 2:32 AM, Rui Barradas wrote: > bootMedianSE <- function(data, indices){ > ???? d <- data[indices, ] > ???? fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) > ???? ypred <- predict(fit) > ???? y <- d$crp > ???? median(y - ypred)^2 > } since the OP is looking for the "median squared error", shouldn't the final line of the

I realize this may be more of a math question. I have the following optim: optim(c(0.0,1.0),logis.op,x=d1_all$SOA,y=as.numeric(md1[,i])) which uses the following function: logis.op <- function(p,x,y) { ypred <- 1.0 / (1.0 + exp((p[1] - x) / p[2])); res <- sum((y-ypred)^2) return(res) } I would like to add weights to the optim. Do I have to alter the logis.op function by

DeaR list, I'm trying to represent some information via 3D plots. My data and session info are at the end of this message. So far, I have tried scatterplot3d (scatterplot3d), persp3d (rgl), persp (graphics) and scatter3d (Rmcdr) but any of them gave me what I'd like to have as final result (please see [1] for a similar 3D plot changing PF by ypred, pdn by h4 and pup by h11). In general

Just checking in to see whether it is intended or not that assigning new formals to a function/closure causes any attributes to be dropped: EXAMPLE: > fcn <- structure(function() {}, foo="foo", class=c("foo")) > str(fcn) function () - attr(*, "srcref")=Class 'srcref' atomic [1:8] 1 18 1 30 18 30 1 1 .. ..- attr(*, "srcfile")=Classes

Greetings, I love the R system and am sincerely grateful for the great effort the product and contributors are delivering. My question is as follows: I am trying to use S4 style classes but cannot write functions that modify an object because paramter passing is by value. For example I want to do this: setGeneric("setData", function(this,fcn,k){ standardGeneric("setData")

Dear R-experts, Doing cross-validation for 2 robust regressions (HBR and fast Tau). I can't get the 2 errors rates (RMSE and MAPE). The problem is to predict the response on the testing data. I get 2 error messages. Here below the reproducible (fictional example) R code. #install.packages("MLmetrics") # install.packages( "robustbase" ) # install.packages(

Dear R useRs, I have a problem with nls.lm function of minpackl.lm package. I need to fit the Van Genuchten Model to a set of data of Theta and hydraulic conductivity with nls.lm function of minpack.lm package. For the first fit, the parameter estimates keep changing even after 1000 iterations (Th) and I have a following error message for fit of hydraulic conductivity (k); Reason for

--rwEMma7ioTxnRzrJ Content-Type: text/plain; charset=us-ascii Content-Disposition: inline R, like recent versions of S-Plus, sometimes - but not always - loses names when subscripting objects with "[". (Earlier versions of S and S-Plus had the correct, name-preserving behavior.) This seems bad, it would be better to remove names only by explicit request, not as an accidental

When batch processing analysis, I use tryCatch() for failure handling and to prevent unwanted interrupts. I write detailed progress to log file and conditions (warnings and errors) are written to the same log file immediately by using withCallingHandlers(..., condition=function(c) cat(c, file=logFile)). However, I would also like to write the call stack to the log file to further simplify

This posting just illustrates the problem with plot() x<-1:20 y<-c(1:10,301:310) plot(x,y) xrange<-c(1,10) plot(x,y,xlim=xrange) #uses ylim=range(y) This is the default behaviour of plot() and I think it is not sensible. By default the range of the y axis should span the y values corresponding to the points plotted. In this example the yaxis should span 1-10 rather than 1-310. This does

Hi all- terribly beginner question here, but I can't figure out how to put dates as the values for my x range in a plot. Example: xrange <- results$current yrange <- results$DIFF plot(xrange, yrange, type="n", xlab="Date", ylab="Differential") lines(results$DIFF, type="l", lwd=1.5, col="red") Where xrange is: > xrange [1]

I thought about that star graph again, and realized that it would be quite a handy thing for visualizing cyclic data like time or compass direction. Here is a cleaned up (and renamed) version to do a polar plot that starts at the right and goes counterclockwise or a 24 hour clock plot that starts at the top and goes clockwise. There are probably other varieties that would be interesting. Jim