similar to: predict.zeroinfl not found

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

Hi: I have tried to find the appropriate clust algorithm for mixed type of data. The suggested way I see is: 1. use daisy to get the dissimilarity matrix 2. use PAM/hclust by providing the dissimilarity matrix, to get the clusters but by following this, when the data set grows bigger say 10,000 rows of data, the dissimilarity matrix will be O(n^2), and out of memory will occur. I am

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]

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]]

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

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:

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 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 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

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

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.

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

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... {

Hello, R for Dummies. How can I exclude the first 1000 values of a vector (length 12000)? More generally all the values up to the ith? Thanks for your help, Dr Olivier Charansonney Cardiologue Centre Hospitalier Sud-Francilien, Corbeil-Essonnes, France [[alternative HTML version deleted]]

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: