2354 search results for "time series"

Like peanut butter and jelly: x13binary and seasonal

February 2, 2016
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Like peanut butter and jelly: x13binary and seasonal

This post was written by Dirk Eddelbuettel and Christoph Sax and posted by both author’s respective blogs. The seasonal package by Christoph Sax brings a very featureful and expressive interface for working with seasonal data to the R environment. It uses the standard tool of the trade: X-13ARIMA-SEATS. This powerful program is provided by the

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Like peanut butter and jelly: x13binary and seasonal

February 2, 2016
By

This post was written by Dirk Eddelbuettel and Christoph Sax and will be posted on both author's respective blogs. The seasonal package by Christoph Sax brings a very featureful and expressive interface for working with seasonal data to the R environment. It uses the standard tool of the trade: X-13ARIMA-SEATS. This powerful program is...

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Cricket analytics with cricketr!!!

January 29, 2016
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Cricket analytics with cricketr!!!

My ebook “Cricket analytics with cricketr’  has been published in Leanpub.  You can now download the book (hot off the press!)  for all formats to your favorite device (mobile, iPad, tablet, Kindle)  from the link  “Cricket analytics with cricketr”. The book has been published in the following formats namely PDF (for your computer) EPUB (for

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R User Groups on GitHub

January 28, 2016
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R User Groups on GitHub

by Joseph Rickert Quite a few times over the past few years I have highlighted presentations posted by R user groups on their websites and recommended these sites as a source for interesting material, but I have never thought to see what the user groups were doing on GitHub. As you might expect, many people who make presentations at...

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Some Comments on Donaho’s “50 Years of Data Science”

January 23, 2016
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Some Comments on Donaho’s “50 Years of Data Science”

An old friend recently called my attention to a thoughtful essay by Stanford statistics professor David Donaho, titled “50 Years of Data Science.” Given the keen interest these days in data science, the essay is quite timely. The work clearly shows that Donaho is not only a grandmaster theoretician, but also a statistical philosopher. The … Continue reading...

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So you want to be a Data Science superstar

January 22, 2016
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So you want to be a Data Science superstar

Big house? Five cars? There’s no one universal way to do it, but get a coffee and read on through this bumper post to find your own way with the advice of real experts. Last summer, Mrs G and I … Continue reading →

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Kaggle: Santa’s Stolen Sleigh

January 22, 2016
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Kaggle: Santa’s Stolen Sleigh

This morning I read Wendy Kan's interesting post on Creating Santa's Stolen Sleigh. I hadn't really thought too much about the process of constructing an optimisation competition, but Wendy gave some interesting insights on the considerations involved in designing a competition which was both fun and challenging but still computationally feasible without military grade hardware. The post

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Modelling With the Generalized Hermite Distribution

January 22, 2016
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Modelling With the Generalized Hermite Distribution

"Count" data occur frequently in economics. These are simply data where the observations are integer-valued - usually 0, 1, 2, ....... . However, the range of values may be truncated (e.g., 1, 2, 3, ....).To model data of this form we typically resort to distributions such as the Poisson, negative binomial, or variations of these. These variations may...

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Learn R From Scratch – Part 3

January 21, 2016
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Learn R From Scratch – Part 3

In the previous tutorial, of the “Learn R From Scratch” series, we learn very important concepts such as lists, dataframes and how to import and export data from R. This time, we will discuss more practical aspects such as exploring built-in datasets, handling dates, writing functions and debugging. In this series, I have also laid

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Learn R From Scratch – Part 2

January 20, 2016
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Learn R From Scratch – Part 2

This is a continuation from the Part 1 of “Learn R From Scratch” series. In the previous post, the videos covered the very basics for R from scratch. We first installed R, got familiar with the environment, worked some basic math, different types of variables, got introduced to vectors and learnt how to access and

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