Several years ago, while a research associate at the University of Chicago, I had the privilege of sitting in on a course taught by Peter Rossi: Bayesian Applications in Marketing and MicroEconometrics. This course -- one I recommend to anyone at U Chicago who is interested in statistics -- was an incredibly clear treatment of Bayesian...
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Call C from R and R from C
Several years ago, while a research associate at the University of Chicago, I had the privilege of sitting in on a course taught by Peter Rossi: Bayesian Applications in Marketing and MicroEconometrics. This course -- one I recommend to anyone at U Chicago who is interested in statistics -- was an incredibly clear treatment of Bayesian...
Error capture
In a recent post to r-sig-ecology, Mike Colvin suggested the following to capture errors within a loop:for (i in 1:1000){fit<-try(lm(y~x,dataset))results<- ifelse(class(fit)=="try-error", NA, fit$coefficients)}
Error capture
In a recent post to r-sig-ecology, Mike Colvin suggested the following to capture errors within a loop:for (i in 1:1000){fit<-try(lm(y~x,dataset))results<- ifelse(class(fit)=="try-error", NA, fit$coefficients)}
Plotting contours
Plenty of packages allow you to plot contours of a "z" value; however, I wanted to be able to plot a specific density contour of a sample from a bivariate distribution over a plot that was a function of the x and y parameters. The example only plots th...
Plotting contours
Plenty of packages allow you to plot contours of a "z" value; however, I wanted to be able to plot a specific density contour of a sample from a bivariate distribution over a plot that was a function of the x and y parameters. The example only plots th...
Drop unused factor levels
When creating a subset of a dataframe, I often exclude rows based on the level of a factor. However, the "levels" of the factor remain intact. This is the intended behavior of R, but it can cause problems in some cases. I finally discovered how to clean up levels in this post to R-Help. Here is an example:
>...Drop unused factor levels
When creating a subset of a dataframe, I often exclude rows based on the level of a factor. However, the "levels" of the factor remain intact. This is the intended behavior of R, but it can cause problems in some cases. I finally discovered how to clean up levels in this post to R-Help. Here is an example:
>...Convert factors to numbers
If you have a vector of factors it is easy to get the factor level; however, I always forget how to extract the factor value. I ran into the answer here.
> x<-factor(c(round(rnorm(10),2),"A","B",NA))
> x
1.61 1.12 1.26 0.09 -0.13 0.16 -0.03 -0.1 0.09 -0.47
A ...
Convert factors to numbers
If you have a vector of factors it is easy to get the factor level; however, I always forget how to extract the factor value. I ran into the answer here.
> x<-factor(c(round(rnorm(10),2),"A","B",NA))
> x
1.61 1.12 1.26 0.09 -0.13 0.16 -0.03 -0.1 0.09 -0.47
A ...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
