similar to: Arimax with intervention dummy and multiple covariates

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 would like to plot a few hundred .csv files. Each file contains one curve with x,y values to plot. I have been searching for "gnu r read many files qplot" and similar words. I found for loops that use assign to generate one variable containing a dataframe. When i uesed the classic "plot' command i could add the curves with something like for... {

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]]

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]

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]]

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, 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 =

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.

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

Dear all, I have just sent an enquiry but probably I hadn’t expressed myself properly. Could anyone help me with the following? When I run the code on my data I get a boxplot with outliers identified by numbers 200 & 201. However, what I would like is to label these outliers with their corresponding “DATA$num” values of the data frame. In this example, the outliers should be labelled as:

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

Hello, Before I start to construct something inferior myself I would like to know if such a plot function is already out there. I have count data of a small survey with a few questions which use a scale from "Strongly disagree" to "Strongly agree" and similar things. What I would like to have for a slide is a plot which shows for each question a line over this scale and the

Dear all, as you can see from the code I want to create *a panel of 11 contour plots through a iteration process*. I found a thread that address the issue of plotting many contour.plots in the same device, but it does not address my problem! I emphasize that the 11 contour plots must be appeared in the same device through an iteration process and NOT individually! par(mfrow=c(4,3)) # I want them

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:

Hello everybody, I have got a data set with about 400 companies. Each company has a score for its enviroment comportment between 0 and 100. These companies belong to about 15 different countries. I have e.g. 70 companies from UK and 5 from Luxembourg,- so the data set is pretty unbalanced and I want to do an ANOVA. Somthing like aov(enviromentscore~country). But the aov function is just for

Hi! I've been looking for a way to calculate std errors of marginal effects when I use interaction terms, but with no success. I pretty much have two cases: continuous variable * continuous variable, and continuous variable * binary variable. In both cases, I know how to calculate the marginal effects, even with simulation. But I still can't figure out how to calculate the std errors of

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

Dear R experts, I have two matrix (seq & mat) & I want to retrieve in a new matrix all the numbers from mat that =1 (corresponding to the same row/ column position) in seq, or all the numbers in mat that =-1 in seq. - Replace all the numbers with NA if it's not 1/-1 in seq. There are some "NA"s in seq. seq=matrix(c(1,-1,0,1,1,-1,0,0,-1,1,1,NA),3,4)

Hi I'm getting an error message with the roots() function in the vars package. Even the example in the help file comes up with an error: > data(Canada) > var.2c <- VAR(Canada, p = 2, type = "const") > roots(var.2c) Error in UseMethod("roots") : no applicable method for 'roots' applied to an object of class "varest" The error is odd, for