search for: pdowney

Hello, I'm running a very long for loop that usually takes hours. For my own piece of mind, it would be nice if I could check periodically and see which iteration the loop is on. A line of code that told R to print the iteration number every 100 or 200 iterations would be perfect. Does anyone know something like this? I've never known how to print anything within a for loop before the

Hello, I have a longitudinal dataset where each individual has a different number of entries. Thus, it is of the following structure: x <- runif(12) id.var <- factor(c(rep("D1",4),rep("D2",2),rep("D3",3),rep("D4",3))) dat <- as.data.frame(x) dat$id.var <- id.var dat > dat x id.var 1 0.9611269 D1 2 0.6738606 D1 3

Hello, I created an array to hold the results of a series of simulations I'm running: d.eta <- array(0,dim=c(3,3,200)) <simulation goes here and populates the array but it's not important> Then I tried to save the results using this: save(d.eta,file="D:/Simulation Results/sim 9-23-11 deta") When I later tried to reload them using this: d.eta <-

...et Impulse Response Functions, so I don't need any fancy cointegration or error correction techniques or any of that). Thanks. P. Mitchell Downey | Research Associate II Justice Policy Center | Urban Institute 2100 M. Street N.W. | Washington, DC 20037 T: (202) 261-5329 | F: (202) 659-8985 PDowney at urban.org | www.urban.org

Hello, A colleague is trying to do a fairly complicated power analysis for a project. The project would be evaluating random assignment to one of three conditions within each of 8 sites. The dependent variable would be binary (we do not care at this point whether it would be analyzed with logit or probit). We can simulate the data in a bunch of iterations and do analyses in each iteration, but

Hello, I hate to ask a question which is directly addressed in the documentation, but can someone please give me an example of how to change the maximum number of iterations used by lmer. I'm having a hard time understanding this: control a list of control parameters. See below for details. control a named list of control parameters for the estimation algorithm, specifying only

Hello, I'm clearly confused about the merge function. In the following r <- merge(x,y,all.x=T,all.y=F) my y vector has only unique values (no duplicates). So I don't understand how this can ever generate an r which is of greater length than x. I thought the default behavior was only matching rows are included, but that using all.x=T included rows with unmatched x's as well. If

Hello, I am using {plm} to estimate panel models. I want to estimate a model that includes fixed effects for time and individual, but has a random individual effect for the coefficient on the independent variable. That is, I would like to estimate the model: Y_it = a_i + a_t + B_i * X_it + e_it Where i denotes individuals, t denotes time, X is my independent variable, and B (beta) is the

Hello, I'm attempting to install the splm package from R-Forge. https://r-forge.r-project.org/R/?group_id=352 The page says, "In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R..." It later says "To install this package directly within R type: install.packages("splm",

Hello, Is there a way to get a single TRUE or FALSE statement from comparing two vectors? For example, c(1,2,3) == c(1,2,3) produces TRUE TRUE TRUE where I would like it to produce only TRUE for use in an if statement. Likewise, when two vectors are not exactly identical (in all elements) I would like a single FALSE result, as opposed to c(1,2,3) == c(1,2,5) TRUE TRUE FALSE Any ideas?

Hello, I'm using dmnorm from the package {mnormt} and getting strange results. First, according to the documentation, dmnorm should return a vector of densities, and I'm only getting one value returned (which is what I would expect). I've been interpreting this as the joint density of all values in the x vector (which is what I want). Should a vector of densities be returned, and if

Hello, I'm running a number of arima models using the "arima" function. Often, when lag length gets too high, these model don't converge and an error message appears as this: > reg <- arima(y,order=c(7,0,7),xreg=isr) Warning message: In arima(y, order = c(7, 0, 7), xreg = isr) : possible convergence problem: optim gave code=1 In this case, when you print the results

Hi, I would like to estimate a VAR of the form: Ay_t = By_t-1 + Cy_t-2 + ... + Dx_t + e_t Where A is a non-diagonal matrix of coefficients, B and C are matricies of coefficients and D is a matrix of coefficients for the exogenous variables. I don't think the package {vars} can do this because I want to include contemporaneous cross-variable impacts. So I want y1_t to affect y2_t and I

Hello, I'd like to simulate data according to an SVAR model in order to demonstrate how other techniques (such as arima) yield biased estimates. I am interested in a 2 variable SVAR with 2 lags (in the notation of the vars vignette, K = 2, P = 2, where B = I_K). I'm using the {vars} package outlined here: http://cran.r-project.org/web/packages/vars/vignettes/vars.pdf I thought that the

Hello, I'd like to plot an empirical cumulative distribution function, except instead of the fraction of values < x, I'd like the fraction of values > x. I think this can be done using the ecdf function in {Hmisc}. I installed the package and loaded it. However, when following the example given in the documentation, I get an error: x <- rnorm(100) ecdf(x,what='1-F')