A Recession Before 2020 Is Likely; On the Distribution of Time Between Recessions

April 19, 2018
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A Recession Before 2020 Is Likely; On the Distribution of Time Between Recessions

I recently saw a Reddit thread in r/PoliticalDiscussion asking the question “If the economy is still booming 2020, how should the Democratic address this?” This gets to an issue that’s been on my mind since at least 2016, maybe even 2014: when will the current period of economic growth end? For some context, the Great…Read more A Recession Before...

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Saddling up; getting on the hoRse for the first time

April 19, 2018
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Saddling up; getting on the hoRse for the first time

Laura Swales, Marketing and Events Assistant This year at Mango we're proudly sponsoring the Bath Cats & Dogs Home. To start our fundraising for them, we decided to run a sweepstake on the Grand National. We asked for £2 per horse, which would go to the cats and dogs home and the winner was promised a bottle of wine for their charitable efforts. Working in...

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Upcoming speaking engagments

April 19, 2018
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Upcoming speaking engagments

I have a couple of public appearances coming up soon. The East Bay R Language Beginners Group: Preparing Datasets – The Ugly Truth & Some Solutions, Tuesday, May 1, 2018 at Robert Half Technologies, 1999 Harrison Street, Oakland, CA, 94612. Official May 2018 BARUG Meeting: rquery: a Query Generator for Working With SQL Data, Tuesday, … Continue reading Upcoming...

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15 Jobs for R users from around the world (2018-04-19)

April 19, 2018
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15 Jobs for R users from around the world (2018-04-19)

To post your R job on the next post Just visit  this link and post a new R job  to the R community. You can post a job for  free  (and there are also “featured job” options available for extra exposure). Current R jobs Job seekers:  please follow the links below to learn more and apply for your R job of interest: Featured Jobs...

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Adding Zero Catches

April 18, 2018
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Introduction Much of my work is with undergraduates who are first learning to analyze fisheries data. A common “learning opportunity” occurs when students are asked to compute the mean catch (or CPE), along with a standard deviation (SD), across multiple gear sets for each species. The learning opportunity occurs because some species will invariably not be caught in some gear...

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rename phylogeny tip labels in treeio

April 18, 2018
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rename phylogeny tip labels in treeio

I don’t know whether ‘rename taxa’ is a common task or not. It seems not a good idea to rename taxa in Newick tree text, since it may introduce problems when mapping the original sequence alignment to the tree. If you just want to show different or additional information when plotting the tree, it is fine and easy to do...

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Latin American R/BioConductor Developers Workshop 2018

April 18, 2018
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Latin American R/BioConductor Developers Workshop 2018

Today I’m excited to invite you to attend the Latin American R/BioConductor Developers Workshop 2018! It’ll be held in Cuernavaca, Mexico from July 30th to August 3rd, 2018. You can find the official announcement in the Bioconductor support website. Let me share with you why I’m excited about this workshop. At BioC2017, Alejandro Reyes and I talked for a while...

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Arrow and beyond: Collaborating on next generation tools for open source data science

April 18, 2018
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Two years ago, Wes McKinney and Hadley Wickham got together to discuss some of the systems challenges facing the Python and R communities. Data science teams inevitably work with multiple languages and systems, so it’s critical that data flow seamlessly and efficiently between these environments. Wes and Hadley wanted to explore opportunities to collaborate on tools for improving interoperability...

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Yet Another Caret Workshop

Yet Another Caret Workshop

IntroYesterday I gave a workshop on applied predictive modelling with caret at the 1st LSE Computational Social Science hackathon. Organiser privileges. I put together some introductory code and started a simple GitHub repo for the participants, so I thought I’d share it here as well. This is not supposed to cover all aspects of caret (plus there is already...

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Performance: when algorithmics meets mathematics

April 18, 2018
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Performance: when algorithmics meets mathematics

In this post, I talk about performance through an efficient algorithm I developed for finding closest points on a map. This algorithm uses both concepts from mathematics and algorithmics. Problem to solve This problem comes from a recent question on StackOverflow. I have two matrices, one is 200K rows long, the other is 20K. For each row (which is...

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Testing multiple interventions in a single experiment

April 18, 2018
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Testing multiple interventions in a single experiment

A reader recently inquired about functions in simstudy that could generate data for a balanced multi-factorial design. I had to report that nothing really exists. A few weeks later, a colleague of mine asked if I could help estimate the appropriate sample size for a study that plans to use a multi-factorial design to choose among a set of...

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Look, something shiny: How to use R Shiny to make Münster traffic data accessible. Join MünsteR for our next meetup!

April 18, 2018
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Look, something shiny: How to use R Shiny to make Münster traffic data accessible. Join MünsteR for our next meetup!

In our next MünsteR R-user group meetup on Monday, June 11th, 2018 Thomas Kluth and Thorben Jensen will give a talk titled Look, something shiny: How to use R Shiny to make Münster traffic data accessible. You can RSVP here: http://meetu.ps/e/F7zDN/w54bW/f About a year ago, we stumbled upon rich datasets on traffic dynamics of Münster: count data of bikes, cars,...

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Summer Interns

April 18, 2018
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We were thrilled by the response to our summer internship program. After carefully reviewing over 250 applications, we have made our final selections. Here is a brief description of each intern and the projects they will be working on this sum...

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R live classes Spring Program – Machine Learning with R & Data viz with R

April 18, 2018
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R live classes Spring Program – Machine Learning with R & Data viz with R

If you want to find the structure hidden behind your data, this is right class for you: you will learn how to group similar observations using Clustering; how to “naturally” aggregate your variables using Dimensionality Reduction; how to predict outcomes using Regression and Classification (LMs, GLMs, Trees, Random forests, Neural networks). In other words, you will get a full-immersion...

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Examining POTUS Executive Orders

April 18, 2018
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Examining POTUS Executive Orders

This week’s edition of Data is Plural had two really fun data sets. One is serious fun (the first comprehensive data set on U.S. evictions, and the other I knew about but had forgotten: The Federal Register Executive Order (EO) data set(s). The EO data is also comprehensive as the summary JSON (or CSV) files... Continue reading →

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Uber overtakes taxis in New York City

April 18, 2018
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Uber overtakes taxis in New York City

In an update to his analysis of taxi and ride-share trips, Todd Schnieder reports that the number of daily Uber rides exceeds the number of taxi rides in New York City, as of November 2017. The data is provided by the New York Taxi and Limousine Commission, and the analysis and graphics were created using the open-source R language....

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setting ggplot2 background with ggbackground

April 18, 2018
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setting ggplot2 background with ggbackground

ggimage 0.1.4 is available on CRAN. This release introduces a new function called ggbackground for setting image background as ggplot canvas. require(ggplot2) p

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Time Series Deep Learning: Forecasting Sunspots With Keras Stateful LSTM In R

Time Series Deep Learning: Forecasting Sunspots With Keras Stateful LSTM In R

Time series prediction (forecasting) has experienced dramatic improvements in predictive accuracy as a result of the data science machine learning and deep learning evolution. As these ML/DL tools have evolved, businesses and financial institutions are now able to forecast better by applying these new technologies to solve old problems. In this article, we showcase the use of a special...

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Sketchnotes from TWiML&AI #124: Systems and Software for Machine Learning at Scale with Jeff Dean

April 17, 2018
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Sketchnotes from TWiML&AI #124: Systems and Software for Machine Learning at Scale with Jeff Dean

These are my sketchnotes for Sam Charrington’s podcast This Week in Machine Learning and AI about Systems and Software for Machine Learning at Scale with Jeff Dean: Sketchnotes from TWiMLAI talk #124: Systems and Software for Machine Learning at Scale with Jeff Dean You can listen to the podcast here. n this episode I’m joined by Jeff Dean, Google Senior Fellow and...

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HH Data Science Meetup slides: Explaining complex machine learning models with LIME

April 17, 2018
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On April 12th, 2018 I gave a talk about Explaining complex machine learning models with LIME at the Hamburg Data Science Meetup - so if you’re intersted: the slides can be found here: https://www.slideshare.net/ShirinGlander/hh-data-science-meetup-explaining-complex-machine-learning-models-with-lime-94218890 Traditional machine learning workflows focus heavily on model training and optimization; the best model is usually chosen via performance measures like accuracy or error and we...

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Le Monde puzzle [#1049]

April 17, 2018
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Le Monde puzzle [#1049]

An algorithmic Le Monde mathematical puzzle with a direct Alice and Bob play a game by picking alternatively one of the remaining digits between 1 and 10 and putting it in either one of two available stacks, 1 or 2. Their respective gains are the products of the piles (1 for Alice and 2 for

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Pencil Scribbles

April 17, 2018
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Pencil Scribbles

Con las bombas que tiran los fanfarrones, se hacen las gaditanas tirabuzones (Palma y corona, Carmen Linares) This time I draw Franky again using an algorithm to solve the Travelling Salesman Problem as I did in my last post. On this occasion, instead of doing just one single line drawing, I overlap many of them … Continue reading Pencil...

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Power analysis for longitudinal multilevel models: powerlmm 0.3.0 is now out on CRAN

April 17, 2018
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My R package powerlmm 0.3.0 is now out on CRAN. It can be installed from CRAN https://cran.r-project.org/package=powerlmm or GitHub https://github.com/rpsychologist/powerlmm. New features This version adds support for raw effect sizes, and new standardized effect sizes using the function cohend(...). Here's an example that use the different types. p

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Data Science Live Book available at Amazon!

April 17, 2018
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Data Science Live Book available at Amazon!

The Data Science Live Book is now available at Amazon! Kindle & Paperback versions! 🚀 Learn Data Science from a practical and intuitive approach using R!

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A one-day course in using Stata and R together: running twice in 2018

April 17, 2018
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A one-day course in using Stata and R together: running twice in 2018

I am going to be giving this course on 10 August and 6 December this year. It is organised by … More

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R FOR HYDROLOGISTS – Seasonality and Trend Decomposition

April 17, 2018
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R FOR HYDROLOGISTS – Seasonality and Trend Decomposition

R FOR HYDROLOGISTS SEASONALITY AND TREND DECOMPOSITION If you don’t have the data, please first get it from the first tutorial here. Also, you need to install and load the ggplot2 package. if(!require(ggplot2)){install.packages(ggplot2, dep=T)} Answers to these exercises are available here. Time series decomposition is a mathematical procedure which transforms a time series into multiple different Related exercise sets:Forecasting: Exponential...

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R Tip: Use Slices

April 16, 2018
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R Tip: Use Slices

R tip: use slices. R has a very powerful array slicing ability that allows for some very slick data processing. Suppose we have a data.frame “d“, and for every row where d$n_observations __ 5 we wish to “NA-out” some other columns (mark them as not yet reliably available). Using slicing techniques this can be done … Continue reading R...

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Reticulated Shiny

April 16, 2018
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Reticulated Shiny

RStudio recently announced the reticulate package, which is designed to help R users inter-operate with Python code. I was immediately excited by this announcement. In a past life, I worked with a team at the National Renewable Energy Lab (NREL) on vehicle simulations. Their models could predict MPG for vehicles based on driving routes. At the time, I had...

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Writing better R functions part four – April 17, 2018

April 16, 2018
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Writing better R functions part four – April 17, 2018

In my last four posts I have been working at automating a process, that I am likely to repeat many times, by turning it into a proper R function. In my last post I overcame some real performance problems, combined two sub-functions into one and generally had a workable piece of code. In the final post in this series...

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