Re: [R] autocorrelation function plot in lattice

Yes. You may use the acf.pacf.plot, tsacfplots and related functions in the HH package. >From ?HH::tsacfplots tsacfplots(co2) acf.pacf.plot(co2) If you want just the acf, and not the pacf also, you can use update(acf.pacf.plot(co2)[1], layout=c(1,1), main="ACF: co2") On Sat,

Re: [R] autocorrelation function plot in lattice

Undoubtedly. Consider nlme::plot.ACF as one possibility. Roll your own is also feasible. -- Sent from my phone. Please excuse my brevity. On August 20, 2016 5:28:04 AM PDT, Naresh Gurbuxani wrote: >Using lattice package, is it possible to plot autocorrelation

[R] Autocorrelation and normal distribution of gaps for ping requests in an unstable network

Hi all I have a powerline network connection which I'm investigating. The test network contains some nodes to which I ping from one host. The source host is always the same and I split the data to get files for each connection. A lot of ping requests get lost and I'm trying to plot an

[R] autocorrelation of a series

Hello all, I have a general question about time series and I wonder if someone could help me. I have time series data of this form: x=c(rnorm(500,0,1),rnorm(500,5,1),rnorm(500,10,1),rnorm(500,3,1),rnorm(500,8,1),rnorm(500,4,1),rnorm(500,1,1),rnorm(500,7,1)) time=1:4000 plot(time,x) Each

[R] Autocorrelation values? How to extract?

Hi, I am attempting to correct my models p-values due to temporal autocorrelations. It is not possible to model the correlation, so I have to make do with the p-value correction. I am feeling a bit thick hereI cannot get the autocorrelation values. What is the argument? My aim is to

Re: [R] Autocorrelation values? How to extract?

Hi Anna, I think you use acf() function to calculate the variable autocorrelation. I'd do: ac - acf(y, lag.max = 100)$acf Here, you use $acf, then you can extract the values only. Best regards, Márcio Diniz PhD Student IME - Mathematical and Statistics Institute USP - University - São Paulo

[R] autocorrelation problem with cointegration

Dear All, I am looking for a cointegration relationship between Spot and Future Price of commodites. The problem i am facing follows: 1. After estimating by Engle-Grranger Method, i found that the residuals are stationary at their level I (o), which is required to fulfill the cointegration test.

[R] Autocorrelation using acf

wrote: From: Prof Brian Ripley rip...@stats.ox.ac.uk Subject: Re: [R] Autocorrelation using library(tseries) To: Vincy Pyne vincy_p...@yahoo.ca Cc: r-help@r-project.org Received: Wednesday, August 24, 2011, 9:08 AM Your understanding is wrong.  For a start, there is no function acf

Re: [R] Autocorrelation using acf

Ripley rip...@stats.ox.ac.uk wrote: From: Prof Brian Ripley rip...@stats.ox.ac.uk Subject: Re: [R] Autocorrelation using library(tseries) To: Vincy Pyne vincy_p...@yahoo.ca Cc: r-help@r-project.org Received: Wednesday, August 24, 2011, 9:08 AM Your understanding is wrong. For a start

[R] Autocorrelation using library(tseries)

Dear R list I am trying to understand the auto-correlation concept. Auto-correlation is the self-correlation of random variable X with a certain time lag of say t. The article http://www.mit.tut.fi/MIT-3010/luentokalvot/lk10-11/MDA_lecture16_11.pdf; (Page no. 9 and 10) gives the methodology

Re: [R] Autocorrelation using library(tseries)

Your understanding is wrong. For a start, there is no function acf() in package tseries: it is in stats. And the autocorrelation at lag one is not the correlation omitting the first and last values: it uses the mean and variance estimated from the whole series and divisor n. Have you

[R] Autocorrelation in R

Hi, I am trying to learn time series, and I am attending a colleague's course on Econometrics. However, he uses e-views, and I use R. I am trying to reproduce his examples in R, but I am having problems specifying a AR(1) model. Would anyone help me with my code? Thanks in advance! Reproducible

Re: [R] Autocorrelation in R

On Wed, 8 Jun 2011, Iuri Gavronski wrote: Hi, I am trying to learn time series, and I am attending a colleague's course on Econometrics. However, he uses e-views, and I use R. I am trying to reproduce his examples in R, but I am having problems specifying a AR(1) model. Would anyone help me

Re: [R] Autocorrelation in linear models

Arni Magnusson arnima at hafro.is writes: I have been reading about autocorrelation in linear models over the last couple of days, and I have to say the more I read, the more confused I get. Beyond confusion lies enlightenment, so I'm tempted to ask R-Help for guidance. Most authors

[R] Autocorrelation in non-linear regression model

Hey all! I am working on my master thesis and I am desperate with my model. It looks as following: Y(t) = β1*X1(t) + β2*X2(t) + δ*(β1*((1+c)/(δ+c))+β2)*IE(t) - β2*α*((1+c)/(δ+c))*(δ+g)* IE(t-1) note: c and g is a constant value The problem I encounter is that between IE(t) and IE(t-1) there

[R] Autocorrelation in linear models

I have been reading about autocorrelation in linear models over the last couple of days, and I have to say the more I read, the more confused I get. Beyond confusion lies enlightenment, so I'm tempted to ask R-Help for guidance. Most authors are mainly worried about autocorrelation in the

[R] Autocorrelation Rho Greater Than One

Dear R Users, Kindly advice me what's wrong in my programming. I'm using the Cochrane-Orcutt two stage procedure with Prais Wisten transformation, below is my R programming : Y-c(60.8,62.5,64.6,66.1,67.7,69.1,71.7,73.5,76.2,77.3,78.8,80.2,82.6,84.3,83.3,84.1,86.4,87.6,89.1,89.3,89.1, , +

Re: [R] autocorrelation in count data

You can fit this model with AD Model Builder's random effects module. there is an example fitting a Poisson and negative binomial to the venerable polio data set with ar(1) random effects at http://admb-project.org/examples/count-data/negative-binomial-serially-correlated-counts A

[R] autocorrelation in count data

hello, I try to model traffic accidents with the following model: glm.nb(y~j+w+m+sf+b+ft,data=fr[]). the problem is that there exist autocorrelation in the data. one possibility is to model traffic accidents with inar(1)-models. has anyone an idea how to change this model in order to

Re: [R] autocorrelation in count data

see http://onlinelibrary.wiley.com/doi/10./j.1467-9892.2010.00684.x/abstract kjetil On Fri, Nov 19, 2010 at 6:02 PM, sa...@hsu-hh.de wrote: hello, I try to model traffic accidents with the following model: glm.nb(y~j+w+m+sf+b+ft,data=fr[]). the problem is that there exist

[R] Autocorrelation with merMCMC object

Hello, *I have some issues with furnction that I've used before and that are not working anymore. I want to check the autocorrelation of an object merMCMC but the function autocorr did not acccept merMCMC object.Is there any ither funtion that I could use?*

[R] Autocorrelation in R for NLS

Hello Can someone please let me know how to test for Autocorrelation in R ( eg. like durbin-watson statistic or any other test) after performing Non linear least squares and what can be the best solution for it. Thanks Regards Ruchita [[alternative HTML version deleted]]

[R] Autocorrelation and t-tests

Hi, I have two sets of data for a given set of (non-lattice) locations. I would like to know whether the two are significantly different. This would be simple enough if it wasn't for the fact that the data is spatially autocorrelated. I have come across several possible solutions (including Cliff

Re: [R] Autocorrelation and t-tests

Hi Bernardo, I suggest you give a look at: Dale MRT Fortin MJ, 2009. Spatial Autocorrelation and Statistical Tests: Some Solutions. Journal of Agricultural, Biological and Environmental Statistics, 14(2):188-206. Cheers milton On Tue, Aug 25, 2009 at 1:08 PM, B Garcia Carreras

Re: [R] autocorrelation

Hi Is any multiple regression-like test with correction for autocorrelation ? If I understand your question, yes. Take a look at the spdep package for starters. Also you may find the following references helpful. Dormann et al. 2007. Methods to account for spatial autocorrelation in the

[R] autocorrelation

Hi Is any multiple regression-like test with correction for autocorrelation ? Wojciech [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide

Re: [R] autocorrelation in gams

On Thu, 2008-08-14 at 16:12 +0100, Abigail McQuatters-Gollop wrote: Hi, I am looking at the effects of two explanatory variables on chlorophyll. The data are an annual time-series (so are autocorrelated) and the relationships are non-linear. I want to account for autocorrelation in my

Re: [R] autocorrelation in gams

Keeping Gavin's advice in mind, you may also want to look at ?acf (and see section 14.1 of MASS) and help(ACF, package=nlme) (see section 5.3 of MEMSS). These are useful functions for exploring the 1d empirical autocorrelation structure of model residuals. hth, Kingsford Jones On Fri, Aug 15,

[R] autocorrelation in gams

Hi, I am looking at the effects of two explanatory variables on chlorophyll. The data are an annual time-series (so are autocorrelated) and the relationships are non-linear. I want to account for autocorrelation in my model. The model I am trying to use is this: Library(mgcv) gam1

Re: [R] autocorrelation error: cannot allocate vector of size 220979 Kb

Thanks. Here are some information about my computer and file: Operating system: Windows 2000 RAM: 1.99 GB After I run the program: gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 468065 12.5 818163 21.9 818163 21.9 Vcells 1160828 8.9 46162021 352.2

[R] autocorrelation in nlme: Error: cannot allocate vector of size 220979 Kb

Dear R community, Below you may find the details of my model (lm11). I receive the error message Error: cannot allocate vector of size 220979 Kb after applying the autocorrelation function update(lm11, corr=corAR1()). lm11-lme(Soil.temp ~ Veg*M+Veg*year, data=a,

Re: [R] autocorrelation error: cannot allocate vector of size 220979 Kb

More information is needed. What is your operating system? How much RAM do you have? Are there other objects in memory that you could delete to recover some space? What does 'str' and 'object.size' say for the data you are analyzing? What does 'gc()' report - you may want to do this

[R] autocorrelation error: cannot allocate vector of size 220979 Kb

Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I have almost 17,000 observations for six years. I can not account for autocorrelation in my model, since I receive the error message after applying

[R] autocorrelation in nlme; Error: cannot allocate vector of size

Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I have almost 17,000 observations for six years. I can not account for autocorrelation in my model, since I receive the error message after applying

Re: [R] autocorrelation in nlme; Error: cannot allocate vector of size

and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -Oorspronkelijk bericht- Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens J S Verzonden: vrijdag 16 mei 2008 23:06 Aan: r-help@r-project.org Onderwerp: [R

Re: [R] autocorrelation in nlme; Error: cannot allocate vector of size

Verzonden: vrijdag 16 mei 2008 23:06 Aan: r-help@r-project.org Onderwerp: [R] autocorrelation in nlme; Error: cannot allocate vector of size Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I

[R] autocorrelation by group in mixed model

Hi all! (How) is it possible to fit a mixed model with group specific auto-correlation structure ? For instance, not all my groups display auto-correlation so I would like to use a corMatrix (corAR1) only for the auto-correlated ones. If I construct manually a the corMatrix, is it possible to

[R] Autocorrelation Matrix

Hi, I am trying to calculate the autocorrelation matrix for an input matrix with the size n*m where n=7 (the dimensionality of my input feature vectors) and m being the time. Thus one could think of the input data as a 7-dimensional time-series. Does anyone know of any way to calculate the