similar to: how to read csv file having variables unequal column sizes

Hi! Suppose I have a dataset as follows pd = c(10,7,10,11,7,11,7,6,8,3,12,7,7,10,10) I wish to calculate the mean, standard deviation, median, skewness and kurtosis i.e. regular standard statistical measures. average = mean(pd) stdev    = sd(pd) median = median(pd) skew    = skewness(pd) kurt     =  kurtosis(pd) Q. No (1) How do I get these at a stretch using some R package? I came across

Dear R helpers   After executing the R code, where the last few lines of the code are something like given below.     ## Part of my R code     n = 20   ........ .........   final_output = data.frame(Numbers = numbers, ABC = data1, XYZ = data2, PQR = data3)           write.csv(data.frame(Scenario = paste("Sc_", 1:n, sep = ""), final_output'), 'result.csv', row.names

Dear R helpers,   I am working on the scenario analysis pertaining to various interest rates. In this connection I need to form the various combinations as under :   Suppose I have two sets A = (a, b, c) and B = (x,y,z)   Then I can easily form the cominations as (ax, ay, az, bx, by, bz, cx, cy, cz)   However, if I have say 5 variables, then total no of possible combinations will be 3^5 = 243.

  Dear R helpers   Suppose I have two sets of ranges (interest rates) as   Range 1 : (7 – 7.50, 7.50 – 8.50, 8.50 – 10.00) with respective probabilities 0.42, 0.22 and 0.36.     Range II : (11-12, 12-14, 14-21) with respective probabilities 0.14, 0.56 and 0.30 respectively.     My problem is to form the combinations of these ranges in a decreasing order of joint probabilities. It is assumed that

Dear 'R' friends I have a sort of stupid question to ask. I have a matrix say of the order 4 X 3 as 83    98    90 21    83    84 70    39    56 65    29    38 Is there any command in R which will reverse the order i.e. I need to have same 4 X 3 matrix but as given below 65    29    38 70    39    56 21    83    84 83    98    90 i.e. the last row becomes first row, second - last row

Dear R helpers   Following is a part of R code.   data_lab <- expand.grid(c("R11", "R12", "R13"), c("R21", "R22", "R23"), c("R31", "R32", "R33"), c("R41", "R42", "R43"), c("R51", "R52", "R53"), c("R61", "R62", "R63"),

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

two OutputsHello! I am Amelia from Auckland and work for a bank. I am new to R and I have started my venture with R just a couple of weeks back and this is my first mail to R-forum. I need following assistance Suppose my R code generates following outputs as > X [[1]] [1] 40 [[2]] [1] 80    160 [[3]] [1] 160   80  400 > Y [[1]] [1] 10 [[2]] [1] 10    30 [[3]] [1] 5  18  20

Dear R helpers   I have some variables say ABC, DEF, PQR, LMN and XYZ. I am choosing any three varaibles at random at a time for my analysis and name these files as input1.csv, input2.csv and input3.csv. So if I choose variables say ABC, DEF and PQR, I am passing the specifications of these variables to input1.csv, input2.csv and input3.csv respectively.   This means in another case even if I

I am fairly new at using R/programming in general so I apologize if I am leaving crucial parts of the puzzle out, but here goes. First and foremost this is the error I am receiving: Error in muPriors[priors[, 1:2]] <- priors[, 3] : NAs are not allowed in subscripted assignments This occurs only when I am using observational priors and some number of nominal variables, it does not

Hello R-sig-debian and (hopefully) Dirk: On Debian wheezy, I have the R packaging that CRAN (you) provide. I run into a little trouble while trying to fiddle with alternative BLAS. I know you and I went around on this last year and I think perhaps I've found something wrong in the framework, or I've just done something wrong. I installed the packages openblas-base and openblas-dev, and

i have time series as 1.3578511 0.5119648 1.3189847 0.9214787 1.2272616 4.9167998 1.2272616 1.2272616 0.8854192 2.3386331 1.6132899 0.2030302 0.8426226 1.2277843 NA 1.3189847 1.3578511 0.8530141 2.3386331 1.0541099 0.7747481 0.5764672 1.3189847 1.2160533 1.2272616 0.6715839 0.9651803 1.6132899 1.2006974 0.6875047 1.3245534 1.2006974 0.8221709 1.3101684 1.6132899 1.6132899 1.2006974 1.3189847

Hello, I?ve tried several times to learn R, but have never gotten past a particular gate. My data are organized by column in Excel, with column headers in the first row. The columns are of unequal lengths. I export them as CSV, then import the CSV file into R. I wish to summarize the data by column. R inserts NA for missing values, then refuses to operate on columns with NA. R is importing

Hi I have used the amelia command from the Amelia R package. this gives me a number of imputed datasets. This may be a silly question, but i am not a statistician, but I am not sure how to combine these results to obtain the imputed dataset to usse for further statistical analysis. I have looked through the amelia and zelig manuals but still can not find the answer. This maybe because I dont

Dear R helpers I have following data stocks <- c("ABC", "DEF", "GHI", "JKL") prices_df <- data.frame(ABC = c(17,24,15,22,16,22,17,22,15,19),                                          DEF = c(22,28,20,20,28,26,29,18,24,21),                                           GHI = c(32,27,32,36,37,37,34,23,25,32),                                          

Dear all. First of all, my english isn't verry good, but I hope I can convey my concern. I've a general question about the Amelia algorithm. I'm no mathematician or statistician, but I had to use R and impute and analyse some data, and Amelia showed results that fitted my expectations. I'll have to defend my choice soon, but I haven't totally grasped what Amelia does. I'm

Hi, I have the following problem- I want to access a list whose elements are imp1, imp2, imp3 etc I tried theusing the paste comand in a for loop see the last for loop below. But I keep calling it df but df = imp1 (for the first run). Any ideas on how I can access the elements of the list? Isaac require(Amelia) library(Amelia) data.use <- read.csv("multiplecarol.CSV", header=T)

Speaking of optimization and speeding up R calculations... I mentioned last week I want to speed up calculation of generalized inverses. On Debian Wheezy with R-2.15.2, I see a huge speedup using a souped up generalized inverse algorithm published by V. N. Katsikis, D. Pappas, Fast computing of theMoore-Penrose inverse matrix, Electronic Journal of Linear Algebra, 17(2008), 637-650. I was so

Dear R-help forum members, Suppose I have a data-frame having two variables and single data for each of them, as described below. variable_1           variable_2         10                          20 I have written a function, say, 'fun' which uses input 10 and 20 and gives me desired result. fun = function(X, Y)          {          X + Y              #( I am just giving an example of

Dear Sir, Thanks for the guidance. Will check. And yes, at the end of each simulation, a large result is getting stored.? Regards Amelia On Wednesday, 6 April 2016 5:48 PM, jim holtman <jholtman at gmail.com> wrote: It is hard to tell from the information that you have provided.? Do you have a list of the sizes of all the objects that you have in memory?? Are you releasing large