similar to: Higher Order Correlation function

> Dear R Helpers! > > bgtest{lmtest} performs the Breusch-Godfrey test for higher > order serial > correlation. > > Is the Higher Order Correlation function already programmed in > R I couldn't find it? > > Sergei Petrov > ?acf ?pacf HTH, Bernhard ---------------------------------------------------------------------- If you have received this e-mail

Hello R-User! I appologise in advance if this should also go into statistics but I am presently puzzled. I have a data.frame (about 300 rows and about 80 variables) and my variables are dichotomous factors, continuous (numerical) and ordered factors. I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm())

Dear all, I didn't find any graphical solution in the package "mva" to plot the canonical scores from a CCA (canonical correlation analysis). Does anybody knows how to plot or has anybody already programmed : - the map of the canonical scores, - the graph of the canonical weights, - the correlation circle i.e. the canonical loadings ? Thank you for help ...

I"ve got a data frame with a selection of columns I want to compute a rank-order correlation matrix from without disturbing the original data frame. foo[,c("a","b","d","f","g")] What I wanted to do, intuitively, was: > cor(rank(foo[,c("a","b","d","f","g")])) but rank in that context

Dear R helpers, Suppose I have stock returns data of say 1500 companies each for say last 4 years. Thus I have a matrix of dimension say 1000 * 1500 i.e. 1500 columns representing companies and 1000 rows of their returns. I need to find the correlation matrix of these 1500 companies. So I can find out the correlation as cor(returns) and expect to get 1500 * 1500 matrix. However, the process

Dear R-help, How could a cross-correlation plot be optimized such that the relationship between seasonal time-series can be studied? We are working with strong seasonal time-series and derived a cross-correlation plot to study the relationship between time-series. The seasonal variation however strongly influences the cross-correlation plot and the plot seems to be ?rather? symmetrical (max

Dear R helpers, I have generated a portfolio of Equity, Dollar Rate and say zero coupon bond. I have calculated the daily returns based on the prices available for last two years. Now, I have three seperate csv files (Equity.csv, Dollar.csv and Bond.csv) containing the respective returns. I need to calculate the correlation matrix between the retuns of these assets. Please guide me how this

Dear R-helpers, This may sound simple to you, but I'm a beginner in this, so please be forgiving. I have a following problem: two analytes were measured in patient's blood on 4 occasions: ProteinA and ProteinB. How to correctly evaluate correlation between ProteinA and ProteinB? I tried: x <- data.frame(Patient.ID=rep(1:10, each=4), Visit=rep(c(1:4),10), ProteinA=rnorm(m=10,

Hello All, I have a panel date - here a small-scale example: df <- data.frame(cbind(rep(c("AUT","BEL","DEN","GER"),4),cbind(rep(c(1999,2000,2001,2002),4)),sample(10,16,replace=T))) names(df) <- c("country","year","x") SORT <- c("GER","BEL","DEN","AUT") I need to compute the

Ok I see how to sort the factors, but how do I compute the correlation matrix in a repeated observations dataset (see the first part of my question) Thanks again for your help! Serge

Hello, I want to compute the pearson's correlation, but even for signals that are shifted. For example having two signals like: 1 1 2 1 1 and 1 2 1 1 1 the correlation is very low.. but if we shift them in the right we get much better correlation. I know that cross-correlation is used to find the best offset (where correlation will be bigger). Is there any metric that can do this job all

Dear r-help members, Can lmer() in the lme4 package fit models that have a specified within-group correlation structure, as provided, for example, by the correlation argument to lme() in the nlme package? Thanks, John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox

Dear R-helpers, I would like to do a Spearman rank order test, and used the cor() function with the method "spearman". It gives me a number (correlation coefficient?) , but how can I get the p-value? Thank you for the help in advance! Regards, Anne-Katrin -- [[alternative HTML version deleted]]

Hi, I am not really familiar with Correlation foundations, although I read a lot. So maybe if someone kindly help me to interpret the following results. I had the following R commands: correlation <-cor( vector_CitationProximity , vector_Impact, method = "spearman", use="na.or.complete") cor_test<-cor.test(vector_CitationProximity, vector_Impact,

Hi all, I have two time series data (say x and y). I am interested to calculate the correlation between them and its confidence interval (or to test no correlation). Function cor.test(x,y) does the test of no correlation. But this test probably is wrong because of autocorrelated data. ccf() calculates the correlation between two series data. But it does not

Hi, To simplify, suppose I have 2 observations each day for three days. I would like to define the correlation structure of these 6 observations as follows: the correlation of 2 observations on the same day is, say, alpha, the correlation for 2 observations one day apart is rho and the correlation for 2 observations 2 days apart is rho^2. I.e. I would like to have an AR1 correlation + a

Hello, I found in the forum two threads about point biserial correlation. One of them (1) mentioned "a point-biserial correlation is just a Pearson correlation where one of the variables is dichotomous. Thus, the command is just the normal cor function". The other (2) mentioned "Professor Fox's package polycor" as a way to calculate point biserial correlation?

[I think I've seen this reported before but can't locate it any more. I believe this oddity (glitch? feature?) is behind a query that Jean-Baptiste Ferdy asked a year ago <http://finzi.psych.upenn.edu/Rhelp08/2008-October/176449.html>] It appears that glmmPQL looks in the global workspace, not within the data frame specified by the "data" argument, for the variables

Hello, If I have two correlation matrices (e.g. one for each of two treatments) and then perform cor() on those two correlation matrices is this third correlation matrix interpreted as the correlation between the two treatments? In my sample below I would interpret that the treatments are 0.28 correlated. Is this correct? > var1<- c(.000000000008, .09, .1234, .5670008, .00110011002200,

Hi everybody. I'm trying to do a correlation matrix in a list of files. Each file contains 2 columns: "capt1" and "capt2". For the example, I merged all in one data.frame. My data also contains many missing data. The aim is to do a correlation matrix for the same data for course (one correlation matrix for capt1 and another for capt2). For the moment, I have a correlation