similar to: qplot with many files (each one curve)

Hi all, I want to test whether the MEAN of two different variables, (and different number of observations) are the same. I am trying to use the anova test but it doesn't seem to like that the number of observations are different: a=c(1:5) b=c(1:3) aov_test=aov(a~b) >>Error in model.frame.default(formula = a ~ b, drop.unused.levels = TRUE) : variable lengths differ (found for

Hello, Is there a function in R by which one can run AR model with Bayesian Information Criteria (BIC)? To my knowledge, functions ar and ar.ols could select the order only by AIC. Thanks, Miao [[alternative HTML version deleted]]

Dear colleagues. I wonder if anybody knows about a procedure in R to calculate the Berger-Parker index and the Brillouin Diversity index. I searched the net but did not find anything good about it. Thanks a lot for any help Mayo, Elvira. [[alternative HTML version deleted]]

Hello, I am totally new in the field of time series analysis and forecasting and R. I read that R is a powerful tool for time series. Could anyone give me navigation what models of time series are availiable in R etc? -- View this message in context: http://r.789695.n4.nabble.com/Time-Series-Analysis-and-Forecasting-tp4646637.html Sent from the R help mailing list archive at Nabble.com.

Hello! I would like to make a scatterplot of my data, but the problem is that several points have the same x and y values and are represented as only one point. I wonder if there is a way to represent the data points, but with point size representing the frequency of the depicted x-y value? Thank you! -- View this message in context:

Dear all, Is there a simple way to add reference lines in background? I am trying with abline() or grid() but the lines, since they are executed after the plot function, are draw on top. How can I draw such lines beneath the main plot? Here is an example: x<-rnorm(100) boxplot(x) abline(h=c(-1,0,1)) grid(NA, 4, lwd = 2) regards, Luigi Marongiu, MSc [[alternative HTML

Dear R users and developers, I have a dataset containing 34 variables measured in a survey, which has some missing items. I would like to conduct a factor analysis of this data. I tested mi, Amelia, and MissForest as alternative packages in order to impute the missing data. I now have 5 separate datasets with the variables I am interested in factor analysing. In my reading of the package

Hi everybody, I am quite new to data imputation, but I would like to use the R package ' Amelia II: A Program for Missing Data '. However, its unclear to me how the input for amelia should look like: I have a data frame consisting of numerous coulmns, which represent different experimental conditions, whereby each column has 3 replicates. I want amelia to perform an imputation across

noob here trying to make boxplots of some data i would like to separate the boxplots according to conditons of various levels for example: i have group:1 and 2, each group performed tests consisting of condition A,B,C,D side: left and right time: 1 to 10 I would like separate boxplots of the results (x) of the tests (numeric) for each group under each condition on each side over time. so far i

Hello everyone, a problem with the plot.zoo function. In the parameters of the function, cex.lab is ignored. I tried to reduce the size of the yaxis labels by at least 50%. ------------------ Example: sample <- as.zoo(EuStockMarkets) par(las=1) plot.zoo(sample, plot.type="multiple", main="Time Series", xlab="Date", yaxt="n", cex.lab=0.5,

Hi, Imagine I have the following data frame: > a <- c(1,NA,3) > b <- c(2,NA,NA) > c <- data.frame(cbind(a,b)) > c a b 1 1 2 2 NA NA 3 3 NA I want to delete the second row. If I use na.omit, that would also affect the third row. I tried to use a loop and an ifelse clause with is.na to get R identify that row in which all records are missing, as opposed to the first

Hi I'm trying to measure the effect of a policy intervention (Box and Tiao, 1975). This query has to do with the coding of the model rather than with the particulars of my dataset, so I'm not providing the actual dataset (or a simulated one) in this case, apart from some general description. The time series are of length n=34 (annual observations between 1977 and 2010). The policy

Dear list members, I would like to create two series of plotted mean values and error bars, yet with different locations along the x-axis. Plotting of first series using plotCI with the standard arguments goes without any problem. However I do not succeed to add the second series in the same plot, which should be horizontally shifted from the first series along the x-axis. The “add=TRUE”

Dear Luigi, Here's an option: boxplot(x, boxcol="white", whiskcol="white",medcol="white",staplecol="white") abline(h=c(-1,0,1)) grid(NA, 4, lwd = 2) boxplot(x,add=T) Regards, Jos? Iparraguirre -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Luigi Sent: 18 September 2012 09:36

Hi Just a quick problem that I hope is simple to resolve. I'm doing some work with zero inflated poisson models using the pscl package. I can build models using zeroinfl and get outputs fom them with no problem, but when I try to use the predict.zeroinfl function, I get Error: could not find function "predict.zeroinfl". I was using an older version of R, but still had the same

Hello all, I tried to extract the p-value from adf.test in tseries; however, I got the error message such as > ht=adf.test(list.var$aa) > ht$p-value Error in ht$p - value : non-numeric argument to binary operator > ht Augmented Dickey-Fuller Test data: list.var$aa Dickey-Fuller = -2.3147, Lag order = 4, p-value = 0.4461 alternative hypothesis: stationary > ht$data [1]

Hello, I wrote a class like so: > rcfdpsuperclass <- setRefClass( > Class="rcfdpsuperclass", > fields = list( > RcfpdVersion = "character"), > methods = list( > initialize = function(){ > 'Populates fields with defaults and lock as appropriate' > initFields( > RcfpdVersion =

Hi all, After running kruskal.test I have got results (p<0,005) pointing to reject the hypothesis that the samples were draw from the same population. Howerver when I run the kruskalmc there are no significant differences in any of the multiple comparisons. Is that possible? Some clarification? Thanks, Humber <https://sites.google.com/site/humberandrade> [[alternative HTML version

I know when I enter this into R: > x = c(15, 10, 13, 7, 9, 8, 21, 9, 14, 8) > y = c(15, 14, 12, 8, 14, 7, 16, 10, 15, 12) > t.test(x,y,alt="less",var.equal=TRUE) it shows: Two Sample t-test data: x and y t = -0.5331, df = 18, p-value = 0.3002 alternative hypothesis: true difference in means is less than 0 95 percent confidence interval: -Inf 2.027436 sample

Hi Experts, As i am a new in this forum, let me introduce myself:- i am Debaranjan, from India, Assam. I have heard many things about R and its statistical Magic feature. i am really have nothing knowledge about R language nor have ever used before. i am only a nursery in R. please help me in learning R. I have gone through many study material for R but have gain nothing