1957 search results for "time series"

Iterators in R

November 13, 2013
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According to Wikipedia, an iterator is “an object that enables a programmer to traverse a container”. A collection of items (stashed in a container) can be thought of as being “iterable” if there is a logical progression from one element to the next (so a list is iterable, while a set is not). An iterator

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A statistical review of ‘Thinking, Fast and Slow’ by Daniel Kahneman

November 11, 2013
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A statistical review of ‘Thinking, Fast and Slow’ by Daniel Kahneman

I failed to find Kahneman’s book in the economics section of the bookshop, so I had to ask where it was.  ”Oh, that’s in the psychology section.”  It should have also been in the statistics section. He states that his collaboration with Amos Tversky started with the question: Are humans good intuitive statisticians? The wrong The post A...

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The R Backpages

November 7, 2013
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The R Backpages

by Joseph Rickert As an avid newspaper reader (I still get the print edition of the New York Times delivered every Sunday morning) I have always thought that some of the most interesting news is to be found in the back pages. So, in that spirit here are some things that I thought might be fit to print. Plotly...

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quantstrat is slow

November 4, 2013
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The complaint I hear most frequently about quantstrat is that it's slow, especially for large data.  Some of this slow performance is due to quantstrat treating all strategies as path-dependent by default.  Path dependence requires rules to b...

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Some Weekend Reading

November 1, 2013
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Just what you need - some more interesting reading! Al-Sadoon, M. M., 2013. Geometric and long run aspects of Granger causality. Mimeo., Universitat Pompeu Fabra. (Forthcoming in Journal of Econometrics.) Barnett, W. A. and I. Kalondo-Kanyama, 2013. Time-varying parameter in the almost ideal demand system and the Rotterdam model: Will the best specification please stand up? Working Paper 335, Econometric...

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Data Preparation – Part I

October 31, 2013
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Data Preparation – Part I

The R language provides tools for modeling and visualization, but is still an excellent tool for handling/preparing data. As C++ or python, there is some tricks that bring performance, make the code clean or both, but especially with R these choices can have a huge impact on performance and the “size” of your code. A The post Data...

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Poisson regression fitted by glm(), maximum likelihood, and MCMC

October 29, 2013
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Poisson regression fitted by glm(), maximum likelihood, and MCMC

The goal of this post is to demonstrate how a simple statistical model (Poisson log-linear regression) can be fitted using three different approaches. I want to demonstrate that both frequentists and Bayesians use the same models, and that it is the fitting procedure and the inference that differs. This is … Continue reading →

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The case for data snooping

October 25, 2013
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The case for data snooping

When we are backtesting automated trading systems, accidental data snooping or look forward errors are an easy mistake to make. The nature of the error in this context is making our predictions using the data we are trying to predict. Typically, it comes from a mistake with our calculations of time offsets somewhere. However, it can be a...

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Knoxville R User’s Group Meeting November 1

October 22, 2013
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Knoxville R User’s Group Meeting November 1

The next meeting of the Knoxville R User’s Group will consist of four 20-minute talks followed by an open planning session. It will take place on Friday, November 1, from 2:00 p.m. to 4:00 p.m. at The University of Tennessee, … Continue reading →

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A Nation of Real Estate Agents

October 20, 2013
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A Nation of Real Estate Agents

I read a series of articles related to the goings of the UK housing market, the likely effects of the new Help To Buy scheme, the 10% increase in mean London house price over the last year, and employment statistics. I failed to reproduce some numbers cited in the economist (below). This post talks about this.It all starts with this...

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