similar to: sliding window over a large vector

I am looking for some help at removing low-frequency components from a signal, through Moving Average on a sliding window. I understand thiis is a smoothing procedure that I never done in my life before .. sigh. I searched R archives and found "rollmean", "MovingAverages {TTR}", "SymmetricMA". None of the above mantioned functions seems to accept the smoothing

[Please keep r-help in the cc: list] I don't quite know how to interpret the difference between specifying effort as an offset vs. as weights; I would have to spend more time thinking about it/working through it than I have available at the moment. I don't know that specifying effort as weights is *wrong*, but I don't know that it's right or what it is doing: if I were

Can someone explain why I am getting the following error: in the r code below? Error in solve.default(diag(2) + ((1/currvar) * (XX1 %*% t(XX1)))) : system is computationally singular: reciprocal condition number = 0 In addition: There were 50 or more warnings (use warnings() to see the first 50) The R code is part of a bigger program. ##sample from full conditional

Dear all, I am stumped at what should be a painfully easy task: predicting from an lm object. A toy example would be this: XX <- matrix(runif(8),ncol=2) yy <- runif(4) model <- lm(yy~XX) XX.pred <- data.frame(matrix(runif(6),ncol=2)) colnames(XX.pred) <- c("XX1","XX2") predict(model,newdata=XX.pred) I would have expected the last line to give me the

Hi All, I am trying to convert the following piece of matlab code to R: XX1 = sum(w(:,ones(1,N1)).*X1.*X1,1); #square the elements of X1, weight it and repeat this vector N1 times XX2 = sum(w(:,ones(1,N2)).*X2.*X2,1); #square the elements of X2, weigh and repeat this vector N2 times X1X2 = (w(:,ones(1,N1)).*X1)'*X2; #get the weighted 'covariance'

Hi there: I have this configuration: |-----[Server 2] | [Internet]--------[Router]----------[Switch]------------ [Server 1] | |-----[PC1] | |-----[PC2] | |-----[PC3] Server 1 has IP 216.251.XXX.XX1 Server 2 has IP 216.251.XXX.XX2 PC1 has IP 216.251.XXX.XX3 PC2 has IP 192.168.XXX.1 PC3 has IP 192.168.XXX.2 How do I configure shorewall in SERVER 2 to block to/from the Internet Port 22

Dear all, I have the following data frame: > raw.count Var1 Freq 1 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA 707 2 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC 14 3 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAT 3 But why when printint it using 'cat', it doesn't print the desired string "AAA" ? > cat(raw.count$Var1,

I''ve made some tests... eth2 is my internal interface, LAN is connected here. Before I had IMQ device in AB mode... PREROUTING [A]fter NAT, POSTROUTING [B]efore NAT. I want the same situation on ifb. I do this in this way: --- # incoming traffic here from LAN is before NAT tc qdisc add dev eth2 handle ffff: ingress # outcoming traffic here from WAN is after NAT tc qdisc add dev eth2

Hello, >I am hoping for some advice as to how I might create a subset of a >matrix. The matrix is 176 x 3530. The rows are individual records >and the columns words. I want to create a new matrix that only >consists of words which occur in at least 5 records. For example, >if column 7 is "charges" and this only appears in 4 records/rows >this variable would not

I'm having problems with the iPhone client in the 1.1.1 version of the iPhone software. Things with other clients work fine, and the iPhone worked fine before it was upgraded to 1.1.1. Other phones on 1.1.1 failed. I'm still working on testing against the client with the iPhone 1.0.2 software on it. The problem is that the client simply doesn't connect to dovecot. I can see the

Hi! > How to do this ?? > To proceed with your answer on PICKUPMARK, where do I put this ??? Look at the example for Asterisk 1.4 on this page: http://www.voip-info.org/wiki/view/Asterisk+cmd+Pickup Philipp

Hello r-help! I have data with two kind of ratings on status of 100 occupations. The first kind of rating is on the percieved "objective" status that these occupations have in society at large, and the second kind or rating is on the status that the respondents think that these occuption *should* have. The ratings were originally integer values in the rage 1-9, but in the current data,

On some systems (alpha), tick marks don't appear on plots. The easiest way to see the problem is something like: > plot(0:1,axes=FALSE) > axis(1,1:2) The problem is in X11_Line(...) from .../src/unix/devX11.c, which is so short I've included the whole function below: static void X11_Line(double x1, double y1, double x2, double y2, int coords, DevDesc *dd) {

Hello All, I have had considerable bad luck with attempting the following with for loops. Here is the problem: # Suppose we have a data.frame with the following data, which can be considered a type of edgelist (for those with networks backgrounds): # # V1 V2 # 1 A # 1 A # 1 B # 2 A # 3 C # 3 A # 3 C # 3 B # # I want the output of the function to produce a matrix, such that #each factor of

Hello dear Samba users, I recently faced an issue with samba (4.10.4) and winbind. The winbind service was stopped, so no user can acces to my samba share. I restart the winbind service, and all users can access to the share as usually... But I would like to understand why this issue occured. My samba server is a centos 7 linux, configured as domain member to a microsoft AD (windows server

Hi, all When I am using mle.cv(wle), I find a interesting problem: I can't do leave-one-out cross-validation with mle.cv(wle). I will illustrate the problem as following: > xx=matrix(rnorm(20*3),ncol=3) > bb=c(1,2,0) > yy=xx%*%bb+rnorm(20,0,0.001)+0 > summary(mle.cv(yy~xx,split=nrow(xx)-1,monte.carlo=2*nrow(xx),verbose=T), num.max=1)[[1]] mle.cv: dimension of the split subsample

Hi, I search a way to replace multiple occurrences of a string with different strings depending on the place where it occurs. I tried the following; x <- c("xx y e d xx e t f xx e f xx") x <- gsub("xx", c("x1", "x2", "x3", "x4"), x) what I want to get is; x = x1 y y e d x2 e t f x3 e f x4 but what I get is; x = x1 y y e

I am trying to understand what rbinom function does. Here is some sample code. Are both the invocations of bfunc effectively doing the same or I am missing the point? Thanks, Pieter bfunc <- function(n1,p1,sims) { c<-rbinom(sims,n1,p1) c } a=c() b=c() p1=.5 for (i in 1:10000){ a[i]=bfunc(30,p1,1) } b=bfunc(30,p1,10000)

Hello, Based on yesterday's R-help thread (help: program efficiency), and following Bill's suggestions, it appeared that sequence: > sequence function (nvec) unlist(lapply(nvec, seq_len)) <environment: namespace:base> could benefit from being written in C to avoid unnecessary memory allocations. I made this version using inline: require( inline ) sequence_c <- local( {

Dear R gurus, As part of finding initial values for a much more complicated fit I want to fit a function of the form y ~ a + bx + cx^d to fairly "noisy" data and have hit some problems. To demonstrate the specific R-related problem, here is an idealised data set, smaller and better fitting than reality: # idealised data set aDF <- data.frame( x= c(1.80, 9.27, 6.48, 2.61, 9.86,