I do reports for clients with LyX and Sweave. It took me an extremely long time to get them working, but now that they’re working I can do more in an hour and thus charge more per hour. If you’re not familiar, here’s a rundown: LaTeX is the stand...

I do reports for clients with LyX and Sweave. It took me an extremely long time to get them working, but now that they’re working I can do more in an hour and thus charge more per hour. If you’re not familiar, here’s a rundown: LaTeX is the stand...

I do reports for clients with LyX and Sweave. It took me an extremely long time to get them working, but now that they’re working I can do more in an hour and thus charge more per hour. (Which is, like, the point.) If you’re not familiar, here’s ...

Consider a (simple) Poisson regression . Given a sample where , the goal is to derive a 95% confidence interval for given , where is the prediction. Hence, we want to derive a confidence interval for the prediction, not the potential observation, i.e. the dot on the graph below > r=glm(dist~speed,data=cars,family=poisson) > P=predict(r,type="response", + newdata=data.frame(speed=seq(-1,35,by=.2))) > plot(cars,xlim=c(0,31),ylim=c(0,170)) > abline(v=30,lty=2)...

The Omega Ratio was introduced by Keating and Shadwick in 2002. It measures the ratio of average portfolio wins over average portfolio losses for a given target return L. Let x.i, i= 1,…,n be weights of instruments in the portfolio. We suppose that j= 1,…,T scenarios of returns with equal probabilities are available. I will

Recently, I've been preparing a poster using the LaTeX packages Beamer and beamerposter. The poster discusses a bunch of R stuff that I've been doing lately, so I successfully used Sweave to incorporate R code into the poster. However, I had some troub...

For this years Halloween I presented the mathematical biology seminar at the Centre for Mathematical Biology. Here is the title and the abstract… Cycles in finite populations: a reproducible seminar in three acts Many natural populations exhibit cyclic fluctuations. Explaining the underlying … Continue reading →

I bought an Android phone, nothing fancy just my first foray in the smartphone world, which is a big change coming from the dumb phone world(*). Everything is different and I am back at being a newbie; this is what … Continue reading →

In the Maximum Loss and Mean-Absolute Deviation risk measures, and Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) posts I started the discussion about alternative risk measures we can use to construct efficient frontier. Another alternative risk measure I want to discuss is Downside Risk. In the traditional mean-variance optimization both returns above and

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