1041 search results for "latex"

Confidence interval for predictions with GLMs

November 4, 2011
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Confidence interval for predictions with GLMs

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)...

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Maximizing Omega Ratio

November 3, 2011
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Maximizing Omega Ratio

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

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Using Sweave with Beamer: A note on fonts

November 2, 2011
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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...

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Cycles in finite populations: A reproducible seminar in three acts

November 1, 2011
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Cycles in finite populations: A reproducible seminar in three acts

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 →

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Teaching with R: the tools

November 1, 2011
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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 →

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Minimizing Downside Risk

November 1, 2011
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Minimizing Downside Risk

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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Sampling for Monte Carlo simulations with R

October 31, 2011
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Sampling for Monte Carlo simulations with R

I've knocked together a quick function for generating efficient Monte Carlo samples. It takes a bit of the legwork out of running Monte Carlo simulations.

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Bayesian ideas and data analysis

October 30, 2011
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Bayesian ideas and data analysis

Here is another Bayesian textbook that appeared recently. I read it in the past few days and, despite my obvious biases and prejudices, I liked it very much! It has a lot in common (at least in spirit) with our Bayesian Core, which may explain why I feel so benevolent towards Bayesian ideas and

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Copulas made easy

October 28, 2011
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Copulas made easy

Everyday, a poor soul tries to understand copulas by reading the corresponding Wikipedia page, and gives up in despair. The incomprehensible mess that one finds there gives the impression that copulas are about as accessible as tensor theory, which is a shame, because they are actually a very nice tool. The only prerequisite is knowing

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The Most Diversified or The Least Correlated Efficient Frontier

October 27, 2011
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The Most Diversified or The Least Correlated Efficient Frontier

The “Minimum Correlation Algorithm” is a term I stumbled at the CSS Analytics blog. This is an Interesting Risk Measure that in my interpretation means: minimizing Average Portfolio Correlation with each Asset Class for a given level of return. One might try to use Correlation instead of Covariance matrix in mean-variance optimization, but this approach,

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