1911 search results for "time series"

Measuring Fat Loss without the scale

July 30, 2014
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Measuring Fat Loss without the scale

@tdhopper posted his self-measurements of weight loss a few months back. I recently decided also that I wanted to lose fat-weight—the infamous “I could stand to be a few kilos lighter”—and I think I came up with a more productive way of thinking about my progress: I’m not going to look at the scale at all....

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Packages vs ProjectTemplate

Packages vs ProjectTemplate tl;dr Imposing a different structure than R packages for distributing R code is a bad idea, especially now that R package tools have gotten to the point where managing a package has become much easier. ProjectTemplate ?? My last two posts (1, 2) provided an argument and an example of why one should use R packages to contain...

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Revisiting package dependencies

July 29, 2014
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Revisiting package dependencies

by Andrie de Vries In my previous post I wrote about how to identify and visualize package dependencies. Within hours, Duncan Murdoch (member of R-core) identified some discrepancies between my list of dependencies and the visualisation. Since then, I fixed the dispecrancies. In this blog post I attempt to clarify the issues involved in listing package dependencies. In miniCRAN...

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Clipping spatial data in R

July 28, 2014
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Clipping spatial data in R

This miniature vignette shows how to clip spatial data based on different spatial objects in R and a ‘bounding box’. Spatial overlays are common in GIS applications and R users are fortunate that the clipping and spatial subsetting functions are mature and fairly fast. We’ll also write a new function called gClip(), that will make clipping by bounding boxes...

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Coherent population forecasting using R

July 23, 2014
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Coherent population forecasting using R

This is an example of how to use the demography package in R for stochastic population forecasting with coherent components. It is based on the papers by Hyndman and Booth (IJF 2008) and Hyndman, Booth and Yasmeen (Demography 2013). I will use Australian data from 1950 to 2009 and forecast the next 50 years. In demography, “coherent” forecasts are...

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Uncovering the Preferences Shaping Consumer Data: Matrix Factorization

July 23, 2014
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Uncovering the Preferences Shaping Consumer Data: Matrix Factorization

How do you limit your search when looking for a hotel? Those trying to save money begin with price. Members of hotel reward programs focus on their brand. At other times, location is first to narrow our consideration set. What does hotel search re...

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Intermission: A Data File For Futures Data (from Quandl)

July 22, 2014
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Intermission: A Data File For Futures Data (from Quandl)

So between variations of different strategies, for those who have yet to come across it, my IKTrading package has a … Continue reading →

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RStudio presents Essential Tools for Data Science with R

July 16, 2014
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RStudio presents Essential Tools for Data Science with R

The RStudio team recently rolled out new capabilities in RStudio, shiny, ggvis, dplyr, knitr, R Markdown, and packrat. The “Essential Tools for Data Science with R” free webinar series is the perfect place to learn more about the power of these R packages from the authors themselves. Click to learn more and register for one or

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Consistent naming conventions in R

July 15, 2014
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Consistent naming conventions in R

Naming conventions in R are famously anarchic, with no clear winner and multiple conventions in use simultaneously in the same package. This has been written about before, in a lucid article in the R Journal, a detailed exploration of names in R source code hosted on CRAN and general discussion on stackoverflow. Basically, there are 5 naming...

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implementing reproducible research [short book review]

July 14, 2014
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implementing reproducible research [short book review]

As promised, I got back to this book, Implementing reproducible research (after the pigeons had their say). I looked at it this morning while monitoring my students taking their last-chance R exam (definitely last chance as my undergraduate R course is not reconoduced next year). The book is in fact an edited collection of papers

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