search for: autocovariate

Hi there, Just wondering why my post was rejected? cheersRachel Subject: repeating autocovariate functions From: r-help-owner@r-project.org To: moyble@hotmail.com Date: Sat, 2 Feb 2013 02:56:27 +0100 Message rejected by filter rule match --Forwarded Message Attachment-- Date: Fri, 1 Feb 2013 17:56:14 -0800 From: moyble@hotmail.com To: r-help@r-project.org Subject: repeating autocovariate...

Hi guys, I'm trying to do the autocovariance of a moving average but it's giving me errors. Here is my code: > w=rnorm(500,0,1) > v=filter(w, sides=2, rep(1/3,3)) > acf(w, lag.max=20) <=that printed out a nice graph. > acf(v, lag.max=20) Error in na.fail.default(as.ts(x)) : missing values in object thanks a lot. -- View this message in context:

If first fit my data column V1 to column V2 using normal "lm" fitting, call it "fit1", then I used "acf(fit1$residuals, type='cov', 40) " function to obtain the autocovariance of the residuals, and then constructed a autocovariance matrix, I chose it to be 40x40. Call this autocovariance matrix B, I then use the following "lm.gls" function to

I started to check what I thought I knew with autocovariance and it doesn’t jive with the the calculations given by ‘R’. I was wondering if there is some scaling or something that I am not aware of. Take the example Ø d <- 1:10 Ø (a <- acf(d, type="covariance", demean=FALSE, plot=FALSE)) Autocovariances of series ‘d’, by lag 0 1 2 3 4 5 6

Hi, I have spatially autocorrelated data (with a binary response variable and continuous predictor variables). I believe I need to do an autologistic model, does anyone know a method for doing this in R? Many thanks C Bell

hello I have covariance stacionary proces, and i want to estimate some parameter of this proces via gmm. My problem is with write "g" -function. 0 order autocovariance is not problem 1 and higher order autocavariance are problem, because add order from 0 mean that I "loose" one "observacion" if I have 100 observation and i am going to use mean, variance and first

I'm a PhD student and I'm working with covariance function. I'm interested to know if exist some packages in R to calculate and plot the bidimensional Autocovariance Function. the input matrix is a matrix that describe a spatial location over a 2-D space and I want to use it in the same way I can use a time serie in the 1-D acf. Thanks, Nicola.

I'm a PhD student and I'm working with covariance function. I'm interested to know if exist some packages in R to calculate and plot the bidimensional Autocovariance Function. the input matrix is a matrix that describe a spatial location over a 2-D space and I want to use it in the same way I can use a time serie in the 1-D acf. Thanks, Nicola.

I am working with amino acid sequences changing each letter to numbers.I have a data from acf transformation called Zm as shown below. I would like to get Indices D1 to D10 and then create F1 to F10 as indicated below. Is there anyway I can do that in R without typing each of them one by one. For example to get D1 to D3, I have to type D1<-c(Zm[[1]])[1][[1]], D2<-c(Zm[[2]])[1][[1]], and

Hi! I just installed R on my computer, and I don't manage to run the function acf (autocovariance and autocorrelation function). It says me that this function is unknown. However, the standard functions like cos or read.table are OK. Can someone help me please? Thanks a lot. Naime -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello, I am trying to calculate the autocovariance matrix for any general farima(p,d,q) with p,q > 1. Could anyone give an idea how to implement in R or if there is any package for this? thank you beforehand. Jose.

Hello expeRts, I need generate symbolize the autocovariances matrix of a Gaussian ARMA(1,1), for derivate it and evaluate. I try this codes, but whitout sucess vacv<-NULL vacv[1]<-1-2*phi*theta-theta^2 vacv[2]<-(1-phi*theta)*(phi-theta) vacv[3:n]<-acv[2]*(phi^(1:(n-2))) facv<-list() for(i in 1:2)

Hello! I have two questions. First of all, I have a problem dealing with acf (Autocovariance function) and need help. First I defined a time series, x, which is a vector created by x <- ts(rnorm(200)). So I plugged the series directly into the acf function, acf(x) and an error message popped up as: Error in .C("acf", as.double(x), as.integer(sampleT), as.integer(nser), :

Hello everyone, I have some binary, spatially autocorrelated data I would like to run autologistic regression on. I hope to incorporate both ordinary covariates (environmental predictors) and a spatial autocovariate in the model, ideally with a second-order neighbourhood structure. Since my computing skills are limited, I am wondering if anyone has composed an algorithm for this purpose, and would be willing to share their work, or at least their insights. My data come with three complications: 1.. I d...

On 11/28/2006 11:50 AM, A.I. McLeod wrote: > Hi Duncan, Hi Ian. > > ccf(x,y) does not explain whether c(k)=cov(x(t),x(t+k)) or d(k)=cov(x(t),x(t-k)) is calculated. The following example demonstrates > that the c(k) definition is used: > ccf(c(-1,1,rep(0,8)),c(1,rep(0,9))) > However S-Plus acf uses the d(k) definition in their acf function. I don't think our code looks

Please pardon me if you see this message twice. The mail server has a bit problem. ***************************************************** Hello! I have two questions. First of all, I have a problem dealing with acf (Autocovariance function) and need help. First I defined a time series, x, which is a vector created by x <- ts(rnorm(200)). So I plugged the series directly into the acf

...y of creating a similar list to the one above, identifying the Presence or Absence of an owl at each of the points that fall with in 0-2000m of the interested site?? I am attempting to determine the following equation for each site, at a number of spatial lags, i.e. 0-2000, 0-4000, etc Autocovariatei = Sum wij yj / Sum wij Variables: Autocovariate for stop i yj = Presence (1) or Absence (0) at stop j wij = the inverse Euclidean distance between stops i and j Any help would be greatly appr...

I need to compute the Fourier transformation of the autocovariance function of a panel composed by 196 time series. With autocovarance function i mean a matrix Gamma(u) which contains the covariance of all the variables at time (t) with all the variables evaluated at time (t-u). It can be represented by a tri-dimensional matrix whose dimensions are (196,196,K), where K is the maximum lag

Dear R-project users I would like to calculate a linear trend versus time taking into account a first order autoregressive process of a single time series (e.g. data$S80 in the following example) using th gls function. gls(S80 ~ tt,data=data,corAR1(value, form, fixed)) My question is what number to set in the position of value within corAR1? Should it be the acf at lag 1? I look forward for

Full_Name: Ian McLeod Version: 2.3.1 OS: Windows Submission from: (NULL) (129.100.76.136) > There is a simple bug in acf as shown below: > > z <- 1 > acf(z,lag.max=1,plot=FALSE) > Error in acf(z, lag.max = 1, plot = FALSE) : > 'lag.max' must be at least 1 > This is certainly a bug. There are two problems: (i) the error message is wrong since lag.max is