Heston model for Options pricing with ESGtoolkit

January 20, 2016
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Heston model for Options pricing with ESGtoolkit

Hi everyone! Best wishes for 2016! In this post, I’ll show you how to use ESGtoolkit, for the simulation of  Heston stochastic volatility model for stock prices. This is probably my last post on ESGtoolkit, before I start working on … Continue reading →

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Who are Turkopticon’s Top Contributors?

January 19, 2016
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Who are Turkopticon’s Top Contributors?

In my most recent post "Turkopticon: Defender of Amazon's Anonymous Workforce" I introduced Turkopticon, the social art project designed to provide basic tools for Amazon's massive Mechanical TURK workforce to share information about employers (requesters).Turkopticon, has a been a runaway success with nearly 285 thousands reviews submitted by over 17 thousand reviewers since its inception in...

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Learn R From Scratch – Part 1

January 19, 2016
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Learn R From Scratch – Part 1

R is an open source programming language with a lot of facilities for problem solving through statistical computing. At the time of writing this, there are more than 6K packages available in CRAN repository. R is a language and an environment for everything related to data analysis. That includes statistical computing, data mining, data analysis,

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miniCRAN – developing internal CRAN Repositories

January 19, 2016
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by Steph Locke Today, I needed to work on a package that had numerous dependencies on internal packages and ones from CRAN. To be able to handle dependencies in the installation process, I needed something like CRAN so that install.packages() … Continue reading →

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Mastering R Plot – Part 1: colors, legends and lines

January 19, 2016
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Mastering R Plot – Part 1: colors, legends and lines

This is the first post of a series that will look at how to create graphics in R using the plot function from the base package. There are of course other packages to make cool graphs in R (like ggplot2 or lattice), but so far plot always gave me satisfaction. In this post we will

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A gentle introduction to parallel computing in R

January 19, 2016
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A gentle introduction to parallel computing in R

by John Mount Ph.D. Data Scientist at Win-Vector LLC Let's talk about the use and benefits of parallel computation in R. IBM's Blue Gene/P massively parallel supercomputer (Wikipedia). Parallel computing is a type of computation in which many calculations are carried out simultaneously." Wikipedia quoting: Gottlieb, Allan; Almasi, George S. (1989). Highly parallel computing The reason we care is:...

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Data Manipulation in R: Beyond SQL

January 19, 2016
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Data Manipulation in R: Beyond SQL

As a follow up to an article on using SQL in R, I just had an new article published at Simple Talk that considers ways to manipulate data in R that are cumbersome in SQL as well as ways to replace SQL statements with functional equivalents.

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Casting a Wide (and Sparse) Matrix in R

January 19, 2016
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I routinely use melt() and cast() from the reshape2 package as part of my data munging workflow. Recently I've noticed that the data frames I've been casting are often extremely sparse. Stashing these in a dense data structure just feels wasteful. And the dismal drone of page thrashing is unpleasant. So I had a look The post

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Formatting table output in R

January 19, 2016
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Formatting table output in R

Formatting data for output in a table can be a bit of a pain in R. The package formattable by Kun Ren and Kenton Russell provides some intuitive functions to create good looking tables for the R console or HTML quickly. The package home page demonstrates the functions with illustrative examples nicely.There are a few points I...

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South Carolina Republican Debate with R

January 19, 2016
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South Carolina Republican Debate with R

Continuing with the series analyzing republican debates, the latest in South Carolina confirms a few of the trends i’ve been observing, mainly that: Trump likes to repeat himself (maybe he likes to stick with what has worked so far?). Trump also likes to keep it short: everyone else says more things for longer at a time. The most...

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Water World

January 18, 2016
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Water World

I live in Utah, an extremely dry state. Like much of the western United States, Utah is experiencing water stress from increasing demand, episodes of drought, and conflict over water rights. At the same time, Utahns use a lot of water per capita compared to residents of other states. According to the United States Geological Survey, in...

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A gentle introduction to parallel computing in R

January 18, 2016
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A gentle introduction to parallel computing in R

Let’s talk about the use and benefits of parallel computation in R. IBM’s Blue Gene/P massively parallel supercomputer (Wikipedia). Parallel computing is a type of computation in which many calculations are carried out simultaneously.” Wikipedia quoting: Gottlieb, Allan; Almasi, George S. (1989). Highly parallel computing The reason we care is: by making the computer work … Continue reading...

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Visualizing Census Estimate Margins of Error in R

January 18, 2016
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Visualizing Census Estimate Margins of Error in R

A key feature of American Community Survey (ACS) data is that the reported values contain both estimates and margins of error. The margins of error, unfortunately, are often overlooked. After meeting with Ezra Glenn last year I gained a new appreciation of them. Today I’ll demonstrate how to visualize them, as well as how they tend to The post

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The Rise of Transparent Data Journalism – The BuzzFeed Tennis Match Fixing Data Analysis Notebook

January 18, 2016
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The Rise of Transparent Data Journalism – The BuzzFeed Tennis Match Fixing Data Analysis Notebook

The news today was lead in part by a story broken by the BBC and BuzzFeed News – The Tennis Racket – about match fixing in Grand Slam tennis tournaments. (The BBC contribution seems to have been done under the ever listenable File on Four: Tennis: Game, Set and Fix?) One interesting feature of this

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MCqMC 2016

January 18, 2016
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MCqMC 2016

After the MCqMC 2014 conference in Leuven I enjoyed very much, the MCqMC 2016 instalment takes place in Stanford this (late) summer. I cannot alas attend it, as I will be in Australia all summer winter, but the program looks terrific! As Art’s tutorial so brilliantly showed at MCMskv last week, the connections between the

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Confidence Regions for Parameters in the Simplex

January 18, 2016
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Confidence Regions for Parameters in the Simplex

Consider here the case where, in some parametric inference problem, parameter  is a point in the Simplex, For instance, consider some regression, on compositional data, > library(compositions) > data(DiagnosticProb) > Y=DiagnosticProb-1 > X=DiagnosticProb > model = glm(Y~ilr(X),family=binomial) > b = ilrInv(coef(model),orig=X) > as.numeric(b) 0.3447106 0.2374977 0.4177917 We can visualize that estimator on the simplex, using > tripoint=function(s){ + p=s/sum(s)...

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Google Geo Data – Data Access Without Restrictions

January 18, 2016
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Google Geo Data – Data Access Without Restrictions

Geo-Distances are of great importance: Researchers from various disciplines refer to geographic distances – health researchers refer to geographic data when analyzing the spread of diseases, economists when evaluating the impact of transaction costs on human behavior, or sociologists when evaluating interpersonal distances (based on external factors) in human interaction. However, each query sent to The post

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ahp 0.2.4 on CRAN

January 18, 2016
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ahp 0.2.4 on CRAN

The latest version of the ahp package contains lots of new features and visualizations! The post ahp 0.2.4 on CRAN appeared first on ipub.

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Scheduling R Markdown Reports via Email

January 17, 2016
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Scheduling R Markdown Reports via Email

R Markdown is an amazing tool that allows you to blend bits of R code with ordinary text and produce well-formatted data analysis reports very quickly. You can export the final report in many formats like HTML, pdf or MS Words which makes it easy to sh...

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stplanr 0.1.1

January 17, 2016
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Version 0.1.1 of the package stplanr has been released on CRAN. This is a major update with many new functions and a new class definition, SpatialLinesNetwork, for route planning and network analysis using igraph. This short post, by myself and package co-author Richard Ellison describes how stplanr can be used for transport research with a few simple...

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Set up RStudio in the cloud to work with GitHub

January 17, 2016
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Set up RStudio in the cloud to work with GitHub

I love GitHub for version control and collaboration, though I'm no master of it. And the tools for integrating git and GitHub with RStudio are just amazing boons to productivity. Unfortunately, my University-supplied computer does not play well with GitHub. Various directories are locked down, and I can't push or pull to GitHub directly from RStudio. ...

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Automating R exercises and exams using the exams package

January 17, 2016
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It's a pain to design statistics exercises each semester, and because students from previous share old exercises with the new incoming students, it's hard to design simple exercises that students haven't already seen the answers to. On top of that, som...

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Nina Zumel and John Mount part of R Day at Strata + Hadoop World in San Jose 2016

January 17, 2016
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Nina Zumel and I are honored to have been invited to be part of Strata + Hadoop World in San Jose 2016 R Day organized by RStudio and O’Reilly. We have written a lot on the topic of model validation in R and we are very excited to distill it down to an exciting tutorial. … Continue reading...

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A simple ANOVA

January 17, 2016
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A simple ANOVA

I was browsing Davies Design and Analysis of Industrial Experiments (second edition, 1967). Published by for ICI in times when industry did that kind of thing. It is quite an applied book. On page 107 there is an example where the variance of a process is estimated.DataData is from nine batches from which three samples were selected (A, B and...

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First step on GIS with R

January 17, 2016
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First step on GIS with R

The PM 2.5 checker written by R has been working nicely for me.  I put a shortcut icon of this small script on my desktop PC, to check the air … Continue reading →

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Creating Calendars for Future’s Expiration

January 17, 2016
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Creating Calendars for Future’s Expiration

Lately I have been doing calendar analysis of various markets (future contracts). Not an overly complicated task, but has a few interesting angles and since I haven’t seen anything similar on the Net – here we go. The world of futures is not friendly – pretty much every contract has its own definition for expiration. The post

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ggtern 2.0 now available

January 16, 2016
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ggtern 2.0 now available

Recently ggplot2 received a severe makeover by releasing version 2.0, and in the spirit of improvement, I thought ggtern should also get an overhaul, so after a few-hundred hours of code review, here is what has changed: Theme elements: Previously, the nomenclature scheme for the new theme elements was a bit all over the shop, The post

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Two Y-Axes

January 16, 2016
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Two Y-Axes

A few days ago, Matt Yglesias shared this tweet from Liz Ann Sonders, Chief Investment Strategist with Charles Schwab, Inc: DailyShot: Here is a comparison of the monetary base with the S&P500 ... Coincidence? pic.twitter.com/QsdNhJdbRP— Liz...

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NBA Stat in a Shiny App

January 16, 2016
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IntroductionShiny app is a new way to present data interactively. Unlike methods like D3, shiny performs complex calculation in real time. As a result, shiny app is more powerful and versatile. However, this also means one cannot simply embed an interactive shiny app in an html document. It needs to be hosted on a shiny server. I rented one...

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