similar to: question reg. conditional regression

(Sorry, sent the message before I finished it) Hello, everyone I have a long script that uses zoo objects. In this script I used simple moving averages and these I can very efficiently calculate with filter() functions. Now, I have to use special "exponential" moving averages, and the only way I could write the code was with a for-loop, which makes everything extremely slow. I don't

Hello, everyone I have a long script that uses zoo objects. In this script I used simple moving averages and these I can very efficiently calculate with filter() functions. Now, I have to use special "exponential" moving averages, and the only way I could write the code was with a for-loop, which makes everything extremely slow. I don't know how to optimize the code, but I need to

I'm trying to do the following out of sample regression with autoregressive terms and additional x variables: y(t+1)=const+B(L)*y(t)+C(1)*x_1(t)...+C(K)*x_K(t) where: B(L) = lag polynom. for AR terms C(1..K) = are the coeffs. on K exogenous variables that have only 1 lag Question 1: ----------- Suppose I use arima to fit the model:

I am trying to interpolate missing values using spline and am running into some strange problems. first, this works just fine: x<- c(1:10, rep(NA, 3), 14:20) y<- c(rnorm(10), rep(NA,3), rnorm(7)) s<- spline(x,y, n=length(x)) plot(x,y) lines(s, col="blue") but look at what happens with my real data (sorry for the long vectors here): x<- c(-9.816, -9.801, -9.801, -9.795,

Dear All, I ave created a public snapshot for use on Amazon EC2 using 64 bit Windows. If you want to try R on multiple cores ,remote desktop you can use this snapshot to create copies. It has R, GUIs for beginners (like RCommander , Deducer- Alas rattle failed due to RGtk+) and a lot of R analytical packages. It also has Chrome for browsing, Adobe Reader for reading help, and a dataset WDI (in

Dear Experts, I am new to R and unfortunately cannot start with a simply statistical analysis: I manually determined the volume of the right and left hippocampus in a group of meditators and in a group of controls. My data-sheet looks as follows: observation subject group age gender hemisphere volume 1 am04 m 25 f left 3.637 2 am04 m 25 f right 3.713 3 ao08 m 47 m left 3.715 4 ao08 m 47

I have a data set for different time intervals. The data has three comment lines before data for each time interval. For each time interval there are 500 data points. I want to change the dataset such that I have the following format: t1 t2 t3 ................ 0.00208 0.00417 0.00625 ................. a1 a2 a3 ...................

Hi List, I have spent more than 30 minutes, but failed to read in this file using the read.table() function. I could not figure out how to fix the following error. Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : line 1 did not have 6 elements Any help would be be appreciated. Thanks, Pradip Muhuri ####### below is the reproducible example xd1 <-

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

Dear all, Does any one knows why should I get the following error message, when trying to do a simple data.frame?? DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS p,DSSp,Slope, CanDens,NearestSp) Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, : arguments imply differing number of rows: 202, 0 The data I am using

Hello, How can an interative unit root test be implemented in R? More specifically, given a time series, I wish to perform the Dickey Fuller Test on a daily basis for say the last 100 observations. It would be interative in the sense that this test would be repeated each day for the last 100 observations. Given the daily Dickey Fuller estimates of delta for the autoregressive process d(Y(t))

Hi everyone, I'm using the HoltWinters() function to do a time series analysis. The function only returns the back fitted values ($fitted) after the first year of data, which is my case, is a little more than half. However, when I use the plot() function, it plots the back fit for almost the entire data set. Any ideas on how to extract the fitted values going all the way back to the start

Dear useRs, how can I construct a box&whisker plot based on the vector "fivenum"? The challenge I face is as follow: I have a table such as x | fivenum --------------- ... | (.....) ... | (.....) and so forth.... For each observation x I have generated a vector containing the fivenum estimates. The first challenge is to group my fivenum vectors into groups based on a

What can I do to UNDERSTAND why, periodically, I can't reach www.centos.org (but everyone else can)? Every few months, http://www.centos.org just drops off for me and for me only. It's not the web site, because I can reach it via a proxy (e.g., TOR browser bundle) and other tests show it to be alive (e.g., http://www.downforeveryoneorjustme.com/centos.org or

I have the following: Time A1 A1 B1 B1 C1 C2 x y x y x y 0 5 6 6 7 7 9 1 3 4 4 3 9 9 2 5 2 6 4 7 4 I want to change it to the following: 0 1 2 x y x y x y A1 5 6 3 4 5 2 B1

Hallo, I have this dataset with repeated measures. There are two within-subject factors, "formant" (2 levels: 1 and 2) and "f2 Ref" (25 levels: 670, 729, 788, 846, 905, 1080, 1100, 1120, 1140, 1170, 1480, 1470, 1450, 1440, 1430, 1890, 1840, 1790, 1740, 1690, 2290, 2210, 2120, 2040, 1950), and one between-subject factor, lang (2 levels:1 and 2). The response variable