similar to: Stock Price Correlation to Index Price Levels

kalish at psy.uwa.edu.au wrote: > > I'm a newbie at R, and can't get libraries to really work. > I did this: > > library(help = mva) > cancor Canonical Correlations > cmdscale Classical (Metric) Multidimensional Scaling > dist Distance Matrix Computation > hclust Hierarchical Clustering

veepsirtt wrote: > > corr <- cor(s1,s2) > Error in cor(s1, s2) : incompatible dimensions > > Check lenghts of your series. cor(c(1,2),c(1,2,3)) #Error in cor(c(1, 2), c(1, 2, 3)) : incompatible dimensions Dieter -- View this message in context: http://r.789695.n4.nabble.com/Finding-the-correlation-coefficient-of-two-stocks-tp3246992p3247042.html Sent from the R help

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

On the cover of Zivot and Wang's Modeling Financial Time Series with S Plus, there is a correlation plot that seems to indicate the strength of correlation with color-coded squares, so that more highly correlated stocks appear darker red. If anybody out there is familiar with the book or understands what I am talking about, I am curious as to whether or not there is a similar function in R

Regarding "financial" data: I have a high frequency (1 minute) measure of supply/demand and I'd like to know if it has any influence on short term price changes (also 1 minute). Question: How do I calculate the correlation between this supply/demand measure and price changes (correctly)? Some facts about that data: The price changes and supply/demand measure are non-normal. An

Hi all i have two data sets, spot and futures cash market prices. to estimate the minimum variance hedge ratio, i first had a glance on the correlation coefficient of relative price change (ln(St / St-1). surprizingly the value is just 0.2 compared to actual price correlation of 0.9. (i did regress the spot change on future change, co-effi is 0.3, and R2 is only 0.025 a) in such scenario can

Hi all: I have a question on how to go about creating a correlation matrix. I have a huge amount of data....21 variables for 3471 times. I want to see how each of the variables correlate to each other. Any help would be appreciated, including which package and which functions I should use to do this. Thanks, Jessica Higgs Masters Student Department of Meteorology Penn State University

Dear list I would like to compare two measurements of disease severity (M1 and M2), one of the is continuous (M1 ranging from 1 to 10) and the other is ordinal (M2 takes Low, Medium, high and very high). Do you think is ok to use cor() function to test whether the two agree, i.e correlate? I am afraid that if I set M2 to 1,2,3 and 4, the function cor() will take them as continuous and

dir1 <- list.files("C:\\Users\\aalyaari\\Desktop\\cor", "*.bin", full.names = TRUE) dir2 <- list.files("C:\\Users\\aalyaari\\Desktop\\cor2", "*.bin", full.names = TRUE) results <- list() for (.files in dir1){ # read in the 365 files as a vector of numbers for dir1 file1 <- do.call(rbind,(lapply(.files, readBin ,

[Apologies in advance if this is too "statistics" and not enough "R".] I've got an experiment with two sets of treatments. Each subject either received all treatments from set A or all treatments from set B. I can compute the N pairwise correlations for all treatments in either set using cor(). If I take the mean of these N pairwise correlations, I see that the effects

Greeting. Dear Mr/Mrs/Miss, OTU ID Health Disease Bacterial 1 0.29 0.34 Bacterial 2 0.25 0.07 Bacterial 3 0.06 0.06 Bacterial 4 0.07 0.09 Bacterial 5 0.02 0.05 Above show the first 6 data sets, may I ask that the reason of R show the error like "Error in cor(data) : 'x' must be numeric" ? And how to solve it? Besides, isn't this data can conduct correlation matrix?

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,

Hello, R gives us the correlation functions cor(). (Many thanks ;-)) Does it also exist a "moving correlation" coefficient ? (like the moving average). If not, could someone give me some infos or link on how to practically implement such a function in R. (I did search for "moving correlation" on the R homepage but didn't find anything.) Thank you. Vincent

Hi, I have a correlation matrix of about 3000 items, i.e., a 3000*3000 matrix. For each of the 3000 items, I want to get the top 50 items that have the highest correlation with it (excluding itself) and generate a data frame with 3 columns like ("ID", "ID2", "cor"), where ID is those 3000 items each repeat 50 times, and ID2 is the top 50 correlated items with ID,

Dear All, I am not familiar with R yet I want to use it to perform some task, hence my posting here. I hope someone can help. I have a set of data, genes (rows) and samples (columns). I want to do a Pearson correlation on all the possible pairwise combinations of all the genes (2000). Does anyone have an idea of how to execute this in R? Thanks in advance. -- View this message in context:

On 2017-07-05 11:56, Jim Lemon wrote: > Hi Chin Yi, > If you are trying to correlate "Health" with "Disease", i.e. > > cydf<-read.table(text="OTU ID Health Disease > Bacterial 1 0.29 0.34 > Bacterial 2 0.25 0.07 > Bacterial 3 0.06 0.06 > Bacterial 4 0.07 0.09 > Bacterial 5 0.02 0.05", > header=TRUE) >

Listers, I have a question regarding correlation matrices. It is fairly straight forward to build a correlation matrix of an entire data frame. I simply use the command cor(MyDataFrame). However, what I would like to do is construct a smaller correlation matrix using just three of the variable out of my data set. When I run this: cor(MyDataFrame$variable1,

Hi Chin Yi, If you are trying to correlate "Health" with "Disease", i.e. cydf<-read.table(text="OTU ID Health Disease Bacterial 1 0.29 0.34 Bacterial 2 0.25 0.07 Bacterial 3 0.06 0.06 Bacterial 4 0.07 0.09 Bacterial 5 0.02 0.05", header=TRUE) print(cor(cydf$Health,cydf$Disease)) [1] 0.7103517 If you are getting that error, it probably means that

Dear group, I have a matrix like the following: Name Sample1 sample2 sample3 sample4 ..... sample(n) nm1 10.5 13.5 30 31 nm2 8 11 34 29 nm3 9 10.3 27.8 35 nm(j) I want to be able to calculate correlation between all pairs of names. For example (nm1,nm2),

Hello, I used the function cor to calculate the pearson correlation coefficient between variables. However, the resulting values do not correspond to the outcome of my excel-calculations, for which I used the formula Cor(x,y)=Cov(x,y)/(SD(x)*SD(y)) So my question is: How does the function "cor" compute the pearson correlation coefficient? Thank you in advance, Ake Nauta