When to use and not to use any particular method of maximization depends to a great extent on the type of data you have. nlm will work just fine if the likelihood surface isn't particularly "rough" ...

Here is one approach using cut() to create the appropriate hourly factors and ddply() from the plyr library for calculating the means. library(lattice) library(plyr) ## Create a record and some ...

Think hard about the underlying data generating process (DGP). If the model you want to use doesn't reflect the DGP, you need to find a new model.

I am the original author of the getSummary.mer function. The reported $p$-values should only be used as a quick check. If I recall, I actually only included the $p$-values to make it work within the ...

Without knowing exactly what you are looking for, using the lattice package you can easily add a loess curve with type="smooth"; e.g., > library(lattice) > x <- rnorm(100) > y <- rnorm(...

When you cluster on some observed attribute, you are making a statistical correction to the standard errors to account for some presumed similarity in the distribution of observations within clusters. ...

According to the man page, svd returns a list with the following elements: d: a vector containing the singular values of x, of length min(n, p). u: a matrix whose columns contain the left ...

What you have is an edge list, which can be converted to a network object using the network library. Here is an example using fictitious data. library(network) src <- c("A", "B", "C", "D", "E", "...

By default, the documentation indicates that rlm uses psi=psi.huber weights. Thus, if you want to use Tukey's bisquare, you need to specify psi=psi.bisquare. The default settings are psi.bisquare(u, c ...

For an overview of some matching algorithms as well as clear examples of applications in everything from education to medical experiments, I would suggest: Paul R. Rosenbaum (2010). Design of ...

As @CliffAB mentions, interpreting changes in the odds on the predicted probabilities scale can be tough. But this is where graphing comes in handy. For instance, let's generate some data following a ...

Donald Green in Yale's political science department has posted the replication data for many of his experiments. You can find them here: Donald Green's Replication Data Green is also the director ...

Looking through some old notes on structural breaks, I have these two cites: Enders, "Applied Econometric Time Series", 2nd edition, ch. 5. Enders discusses interventions, pulse functions, gradual ...

If you are interested in the amount of time it takes to complete an order, it seems that a duration analysis (aka survival or event history analysis) would be most appropriate. See the Wikipedia entry ...

Thank you for the clarification, B_Miner. I don't do a lot of forecasting myself, so take what follows with a pinch of salt. Here is what I would do as at least a first cut at the data. First, ...