similar to: Where to find the p-value of a correlation test

Hello All, I cant seem to do a trig regression in R. The equation is as follows : y = a+b*(sin((2*pi*x/360) - c))^2 a, b, c are coefs that I want. y, x are input vectors. The equation I put into R: lm(y ~ sin(2*pi*x/360)^2) This equation is missing the c and I dont get the right answer. Also, I dont know how to plot the lm over the x values instead of the indices. Any help is sincerely

Hello all, I recently installed rpy2 so that I could use R through Python. However, R was not recognized in the command line. So I decided to add it to the PATH variables. But it just doesnt work.... And what I mean by it doesnt work is : No matter what I type at the prompt in DOS- be it R, Rcmd, R CMD, Rscript- it is not recognized as a command. Path variables used : 1. %R_HOME% -->

Hello All, Does anyone know how to download historical LIBOR rates of different currencies into R? Or if anyone knows of a website that holds all this data...I only need up to january of 2000. Also, how can we make the row names the index of a plot (the names of the x values)? [[alternative HTML version deleted]]

Hi, I have a problem with the time formatting in R. I have entered time in the format "MM:SS.xyz" and R has automatically classified this as a factor, but I need it numerically. However when I use as.numeric() it gives me totally different numbers. Is there any way I can tell R to read thes input as a number? Thank you very much [[alternative HTML version deleted]]

Dear community I'm pretty new to R and I'm trying to do a Point-baserial correlation for a nominal dichotomous variable with a interval scaled variable. It works fine, but the output just shows me the correlation and nothing else (p-Value would be important). I tried it with the following codes: - biseral.cor() - cor.biseral() - I also tried a polyserial() I've found on this

Hello all, I've run a Spearman's Rank test to discern relationships between landscape characteristics and a specific aspect of river behaviour. I've executed a correlation matrix between the one dependent variable and all of the predictors, which gives me a nice output of Spearman's Rho values. However, I also need to somehow find the "p" value, to assess the strength

Guys, I wrote to the finance mailing list earlier with my questions but was directed here. Sorry for the repeat. --------------- library(quantmod) .... now <- Sys.time() midnight <- strptime() # <---- I want to make this a static variable that will be equal to 12:00:00 am but I dont know what to put here. I keep getting NA for everything I do if(now == midnight) {

My two matrices are roughly the sizes of m1 and m2. I tried using two apply and cor.test to compute the correlation p.values. More than an hour, and the codes are still running. Please help to make it more efficient. m1 <- matrix(rnorm(100000), ncol=100) m2 <- matrix(rnorm(10000000), ncol=100) cor.pvalues <- apply(m1, 1, function(x) { apply(m2, 1, function(y) { cor.test(x,y)$p.value

I'm hoping there is a simple answer to this - it seems that there should be, but I can't figure it out. I have a matrix/data frame with three variables of interest - V1, V2, V3. One, V1, is a factor with x levels (x may be a large number); I want to calculate the correlation between the other two (i.e. cor(V2,V3)) for each level, and store it as a vector of length x. I should think this

Respected Sir, I am trying to import excel file into R, but I need to truncate some columns from the original file. How to delete unwanted columns when I import data from excel file. How to use cor.test for the data when I want the output rowwise. How to do grouping and use cor.test on that data I need some help regarding how to calculate the correlation. I don't know whether you

I have to admit that I'm at a bit of a loss here; any pointers would be greatly appreciated. I've been making correlation matricies from some of my datasets, and have been instructed to get the probability values for each of these correlations. I've checked the online help for info on both the cor and cov functions, but I was unable to find any relevant info on finding how to obtain

I have two data matrices that I want to make the correlation between each column from data1 and each column from data 2 and also calculate the p-value Matrices dont have the same size and I tried such a script. > bg <- read.table (file.choose(), header=T, row.names) > bg > Otu00022 Otu00029 Otu00039 Otu00042 Otu00101 Otu00105 Otu00125 Otu00131 Otu00137 Otu00155 Otu00158 Otu00172

Friends I am new to R (and statistics) so am struggling a bit. Briefly... I am interested in getting the P-Value from cor(X) where X is a matrix. I have found cor.test. Verbosely... I have 4 vectors and can generate the corellation matrix... > cor(cbind(X1, X2, X3, X4)) X1 X2 X3 X4 X1 1.00000000 -0.06190365 -0.156972795 0.182547517 X2

I apologize for how basic a question this is. I am a Stata user who has begun using R, and the syntax differences still trip me up. The most basic questions, involving as they do general terms, can be the hardest to find solutions for through search. Assume for the moment that I have a dataset that contains seven variables: Pollution, Temp, Industry, Population, Wind, Rain and Wet.days. (This

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,

Dear mailing list member I have got the following question: The function "cor.test(x1, x2)$p.value" computes the statistical significance of the correlation between vectors x1 and x2. However, I have got a data matrix with many variables. Instead of typing in all possible combinations, I was wondering if there is perhaps an R-function that produces a matrix showing the

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]]

Hello, I do not understand the correct way to approach the following problem in R. I have observations of pairs of variables, v1, o1, v2, o2, etc, observed every 30 seconds. What I would like to do is compute the correlation matrix, but not for all my data, just for, say 5 minutes or 1 hour chunks. In sql, what I would say is select id, date_trunc('hour'::text, ts) as tshour,

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 studying some process measurement time series in R and trying to identify time delays using cross-correlation function ccf. The results have however been bit confusing. I found a couple of years old message about this issue but unfortunately wasn't able to find it again for a reference. For example, an obvious time shift is observed between the measurements y1 and y2 when the