Naive Principal Component Analysis (using R)

September 7, 2017
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Naive Principal Component Analysis (using R)

Post from Pablo Bernabeu’s blog. Principal Component Analysis (PCA) is a technique used to find the core components that underlie different variables. It comes in very useful whenever doubts arise about the true origin of three or more variables. There are two main methods for performing a PCA: naive or less naive. In the naive method, … Continue reading Naive...

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In case you missed it: August 2017 roundup

September 7, 2017
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In case you missed them, here are some articles from August of particular interest to R users. Using the featurizeText function in the MicrosoftML package to extract ngrams from unstructured text. A joyplot visualizes the probabilities associated with phrases like "highly likely" and "little chance" by a sample of 46 Redditors. Two examples of creating 3-D animations in R:...

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Combined Linear Congruential Generators with R

September 7, 2017
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Combined Linear Congruential Generators with R

Part of 3 in the series Random Number GenerationCombined linear congruential generators, as the name implies, are a type of PRNG (pseudorandom number generator) that combine two or more LCGs (linear congruential generators). The combination of two or more LCGs into one random number generator can result in a marked... The post Combined Linear Congruential Generators with R appeared first...

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Less than a week to go: EARL London 2017

September 7, 2017
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Less than a week to go: EARL London 2017

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Looking for a new research assistant

September 7, 2017
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I’m currently looking for a new research assistant to help (primarily) with some modelling and R coding as part of a project on forecasting mobile phone sales. The position is likely to last for about 6–9 months, and will be casual. Requirements Based in Melbourne. I’d rather not communicate remotely. Able to work at least 20 hours per...

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A Data Visualization Work in Progress

September 7, 2017
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A Data Visualization Work in Progress

Data Visualization for Social Science: A Practical Introduction with R and ggplot2 ...

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Text Message Classification

September 7, 2017
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Text Message Classification

Classification is a supervised machine learning technique in which the dataset which we are analyzing has some inputs \(X_i\) and a response variable \(Y\) which is a discrete valued variable.Discrete valued means the variable has a finite set of values.In more specific terms in classification the response variable has some categorical values.In R we call Related Post Analyzing Google Trends...

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SVG from stats software: the good, the bad and the ugly

September 7, 2017
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SVG from stats software: the good, the bad and the ugly

What and why If there could only be one file format to save your charts in, it should be SVG. … More

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Spelling 1.0: quick and effective spell checking in R

September 7, 2017
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The new rOpenSci spelling package provides utilities for spell checking common document formats including latex, markdown, manual pages, and DESCRIPTION files. It also includes tools especially for package authors to automate spell checking of R documentation and vignettes. Spell Checking Packages The main purpose of this package is to quickly find spelling errors in R packages. The spell_check_package() function extracts all...

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Analysing soil moisture data in NetCDF format with the ncdf4 library

September 6, 2017
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Analysing soil moisture data in NetCDF format with the ncdf4 library

The netCDF format is popular in sciences that analyse sequential spatial data. It is a self-describing, machine-independent data format for creating, accessing and sharing array-oriented information. The netCDF format provides spatial time-series such as meteorological or environmental data. This article shows how to visualise … Continue reading → The post Analysing soil moisture data in NetCDF format with the ncdf4 library appeared first on...

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It’s tibbletime: Time-Aware Tibbles

September 6, 2017
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It’s tibbletime: Time-Aware Tibbles

We are very excited to announce the initial release of our newest R package, tibbletime. As evident from the name, tibbletime is built on top of the tibble package (and more generally on top of the tidyverse) with the main purpose of being able to crea...

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RStudio 1.1 Preview – New Features in RStudio Server Pro

RStudio 1.1 Preview – New Features in RStudio Server Pro

Today, we’re continuing our blog series on new features in RStudio 1.1. If you’d like to try these features out for yourself, you can download a preview release of RStudio Server Pro 1.1. RStudio Server Pro Today we are going to be talking about some of the great new features we have added to RStudio Server Pro v1.1, which make...

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Some thoughts about Bayesian Kriging in INLA

September 6, 2017
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Some thoughts about Bayesian Kriging in INLA I have been playing around with spatial modelling in the R INLA package. This blog just records a few thoughts I have had about using INLA for kriging (spatial interpolation). I am keen to discuss these ide...

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rOpenSci OzUnconference coming to Melbourne

September 6, 2017
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For a second year running, there will be another rOpenSci OzUnconference in Australia. This one will be held in Melbourne, on 26-27 October 2017. Unlike regular conferences, there are no talks and there is no pre-determined agenda. It brings together s...

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Knime 3.4 connections to Microsoft R, Azure

September 6, 2017
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Version 3.4 of the Knime Analytics Platform, the open-source data science workflow toolbox, was released back in July. With that release came new integrations with Azure and Microsoft R Server, which were highlighted in a recent blog post. With Knime 3.4, you can use Microsoft R Server packages in an R node, and connect to data services in Azure....

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Envisioning Data Science Webinar Series and Call for Input

September 6, 2017
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Envisioning Data Science Webinar Series and Call for Input

Webinar Series: Data Science Undergraduate Education Join the National Academies of Sciences, Engineering, and Medicine for a webinar series on undergraduate data science education. Webinars will take place on Tuesdays from 3-4pm ET starting onSeptember 12 and ending on November 14. See below for the … Continue reading →

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New Statistics Course: Multiple and Logistic Regression!

September 6, 2017
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New Statistics Course: Multiple and Logistic Regression!

Hi there! We just launched a new course: Multiple and Logistic Regression by Ben Baumer! In this course, you'll take your skills with simple linear regression to the next level. By learning multiple and logistic regression techniques you will gain the...

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The Ultimate Guide To Partitioning Clustering

September 6, 2017
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The Ultimate Guide To Partitioning Clustering

In this first volume of symplyR, we are excited to share our Practical Guides to Partioning Clustering. The course materials contain 3 chapters organized as follow: K-Means Clustering Essentials Contents: K-means basic ideas K-means algorithm ...

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Mapping the largest cities in Asia using R

September 6, 2017
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Mapping the largest cities in Asia using R

"After you've mastered a small number of R functions, visualizations like this become easy (and, they're great practice)." The post Mapping the largest cities in Asia using R appeared first on SHARP SIGHT LABS.

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Beyond the basics of data.table: Smooth data exploration

September 5, 2017
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Beyond the basics of data.table: Smooth data exploration

This exercise set provides practice using the fast and concise data.table package. If you are new to the syntax it is recommended that you start by solving the set on the basics of data.table before attempting this one. We will use data on used cars (Toyota Corollas) on sale during 2004 in the Netherlands. There Related exercise sets: Basics of...

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RStudio Connect v1.5.6 – Now Supporting Kerberos!

September 5, 2017
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RStudio Connect v1.5.6 – Now Supporting Kerberos!

We’re pleased to announce support for Kerberos in RStudio Connect: version 1.5.6. Organizations that use Kerberos can now run Shiny applications and Shiny R Markdown documents in tailored processes that have access only to the appropriate resources inside the organization. The notable changes this release include: Full support for Kerberos across Shiny applications and Shiny R Markdown documents by running R...

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Data Science for Fraud Detection

September 5, 2017
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Data Science for Fraud Detection

I have written the following post about Data Science for Fraud Detection at my company codecentric’s blog: Fraud can be defined as “the crime of getting money by deceiving people” (Cambridge Dictionary); it is as old as humanity: whenever two...

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Blocked Gibbs Sampling in R for Bayesian Multiple Linear Regression

September 5, 2017
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Blocked Gibbs Sampling in R for Bayesian Multiple Linear Regression

In a previous post, I derived and coded a Gibbs sampler in R for estimating a simple linear regression. In this post, I will do the same for multivariate linear regression. I will derive the conditional posterior distributions necessary for the blocked Gibbs sampler. I will then code the sampler and test it using simulated … Continue reading Blocked...

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Preview of EARL London 2017

September 5, 2017
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The next event in the Effective Applications of the R Language (EARL) conference series takes place next week, with EARL London 2017. The EARL conference series got its start in London, and the London event remains the biggest and brightest of the venues. This year's program is no exception, with an impressive raft of tutorials and keynote speakers, and...

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Upcoming talk at the Association of Public Data Users (APDU) Conference

September 5, 2017
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Upcoming talk at the Association of Public Data Users (APDU) Conference

On Thursday, September 14th I will be giving a lightning talk at the Association of Public Data Users (APDU) Conference in Alexandria, Virginia. The talk... The post Upcoming talk at the Association of Public Data Users (APDU) Conference appeared first on AriLamstein.com.

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Leverage Up When You’re Down?

September 5, 2017
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Leverage Up When You’re Down?

This post will investigate the idea of reducing leverage when drawdowns are small, and increasing leverage as losses accumulate. It’s … Continue reading →

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Mining Your Routine Data for Reference Intervals: Hoffman, Bhattacharya and Maximum Likelihood

September 5, 2017
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Mining Your Routine Data for Reference Intervals: Hoffman, Bhattacharya and Maximum Likelihood

Background Let me preface this by saying I am not making a recommendation to use the Hoffman method. Neither am I advocating for reference interval mining from routine data. There are many challenges associated with this kind of effort. That's for another post I think. However, I am going to how one does the calculations … Continue reading Mining...

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cdparcoord: Parallel Coordinates Plots for Categorical Data

September 4, 2017
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cdparcoord: Parallel Coordinates Plots for Categorical Data

My students, Vincent Yang and Harrison Nguyen, and I have developed a new data visualization package, cdparcoord, available now on CRAN. It can be viewed as an extension of the freqparcoord package written by a former grad student, Yingkang Xie and myself, which I have written about before in this blog. The idea behind both … Continue reading cdparcoord:...

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Nested Resampling with rsample

September 4, 2017
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Nested Resampling with rsample

A typical scheme for splitting the data when developing a predictive model is to create an initial split of the data into a training and test set. If resampling is used, it is executed on the training set where a series of binary splits is created. In rsample, we use the term analysis set for the data that...

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