2311 search results for "time series"

Interpreting Confidence Intervals – new d3.js visualization

November 28, 2014
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Interpreting Confidence Intervals – new d3.js visualization

I just published a new interactive visualization in my series of basic statistical concepts and techniques. This time I have tried to explain confidence intervals for means. This visualization shows a simulation of repeated sampling from a normal dist...

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analyze the national longitudinal surveys (nls) with r

November 25, 2014
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as the oldest panel survey out there, the bureau of labor statistics' national longitudinal surveys (nls) have been operating so long that justin bieber's grandparents might be too young (and also too legally canadian) to have participated in the initi...

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Synchronization for R with the flock Package

November 20, 2014
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Have you tried synchronizing R processes? I did and it wasn’t straightforward. In fact, I ended up creating a new package – flock. One of the improvements I did not too long ago to my R back-testing infrastructure was to start using a database to store the results. This way I can compute all interesting

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Partying R Style with Sqor Sports, R on Azure, and data.table

November 20, 2014
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Partying R Style with Sqor Sports, R on Azure, and data.table

by Joseph Rickert We usually have a pretty good time at the monthly Bay Area useR Group (BARUG) meetings, but this month's meeting was a bit more of a party than usual. The very well connected PR team at Sqor Sports, our host company for the evening, secured San Francisco's tres trendy 111 Minna Gallery for the venue. There...

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Reinterpreting Lee-Carter Mortality Model

November 18, 2014
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Reinterpreting Lee-Carter Mortality Model

Last week, while I was giving my crash course on R for insurance, we’ve been discussing possible extensions of Lee & Carter (1992) model. If we look at the seminal paper, the model is defined as follows Hence, it means that This would be a (non)linear model on the logarithm of the mortality rate. A non-equivalent, but alternative expression...

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SAS PROC MCMC example in R; Poisson Regression

November 16, 2014
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In this post I will try to copy the calculations of SAS's PROC MCMC example 61.5 (Poisson Regression) into the various R solutions. In this post Jags, RStan, MCMCpack, LaplacesDemon solutions are shown. Compared to the first post in this series, rcppbugs and mcmc are not used. Rcppbugs has no poisson distribution and while I know how to...

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analyze the national incident-based reporting system (nibrs) with r and monetdb

November 11, 2014
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in 2012, more than one quarter of the united states population lived in the jurisdiction of a police department that submitted details about every crime to a central repository maintained by the fbi.  a production of the uniform crime reports (ucr) program, the national incident-based reporting system (nibrs) compiles statistics from police agencies in thirty five states...

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solar navigation

November 9, 2014
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solar navigation

Introduction Solar altitude is a function of time, longitude and latitude, and so it can be possible to infer location based on measuring altitude as a function of time. This form of solar navigation can be based on sunrise and sunset times, at least on non-equinox days. I have explored this for a school-based project I call “SkyView” involving light sensors and Arduino microcontrollers,...

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Evaluating BreakoutDetection

November 6, 2014
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Evaluating BreakoutDetection

A couple of weeks ago, Twitter open-sourced their BreakoutDetection package for R, a package designed to determine shifts in time-series data. The Twitter announcement does a great job of explaining the main technique for detection (E-Divisive with Medians), so I won’t rehash that material here. Rather, I wanted to see how this package works relative

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Looking into a very messy data set

November 6, 2014
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Looking into a very messy data set

by Joseph Rickert I recently had the opportunity to look at the data used for the 2009 KDD Cup competition. There are actually two sets of files that are still available from this competition. The "large" file is a series of five .csv files that when concatenated form a data set with 50,000 rows and 15,000 columns. The "small"...

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