[R] creating dummy variables based on conditions

Hello everyone, I have a dataset which includes the first three variables from the demo data below (year, id and var). I need to create the new variable ans as follows If var=1, then for each year (where var=1), i need to create a new dummy ans which takes the value of 1 for all corresponding

Re: [R] creating dummy variables based on conditions

1 #4 2010 1 0 1 1 #5 2011 2 1 1 1 #6 2011 2 0 1 1 #7 2011 1 0 0 0 #8 2011 1 0 0 0 A.K. - Original Message - From: Anup Nandialath anupme...@gmail.com To: r-help@r-project.org Cc: Sent: Sunday, July 14, 2013 7:30 AM Subject: [R

Re: [R] Help on loops

Thanks Jim! --- On Tue, 12/7/10, jim holtman jholt...@gmail.com wrote: From: jim holtman jholt...@gmail.com Subject: Re: [R] Help on loops To: Anup Nandialath anup_nandial...@yahoo.com Cc: r-help@r-project.org Date: Tuesday, December 7, 2010, 7:47 PM use split and lapply to make it easier

[R] Constraints when sampling from a distribution

 Dear R-helpers, My question is related to how to impose constraints when when sampling from a distribution. For example, suppose I'm sampling a vector from a multivariate normal distribution vbeta - 100*diag(2) mbeta - c(1,1) ans - beta - c(rmvnorm(1,mbeta,vbeta)) ans will thus be a vector

[R] Help on loops

Dear R-helpers, I have a basic question on using loops. I have a panel data set with different variables measured for n firms over t time periods. A snapshot of the data is given below id    t    X1    X2 1    1     4    3 1    2    9    2 1    3    7    3 1    4    6    6 2    1    6    4 2  

Re: [R] Metropolis acceptance rates

Hi Michael, If you are using the standard logit or probit model, it is fairly easy to save the acceptance rate after each draw. I would recommend using the bayesm package as the source code is easy to manipulate. For instance in the probit function (rbprobitGibbs), you need to include a

[R] Rejection sampling to draw from distributions

Dear friends, Please find below the code that I have employed for a rejection sampler to draw from asymmetric laplace distributions. I was wondering if this code can be written more efficiently? Are there more efficient ways of drawing random numbers from asymmetric laplace distributions??

[R] Bootstrapping

Dear friends, I'm interested in obtaining bootstrapped standard errors for a model that I'm estimating. I do realize that i can use the sample command and do the bootstrap by hand. But I was hoping somebody can help me on how to use the boot package. The model is as follows # Likelihood

[R] Is there a simpler way to do this?

Dear Friends, My objective is to do element wise multiplication of two vectors. For example suppose I have a - (1,1,1) b - (2,4) My output should be (2,4,2,4,2,4). I managed to write it down with loops as follows r - c(1,1,1) l - c(2,4) x - 1 for (j in 1:3) { for (i in 1:2) {