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Data Science, Data Mining and Predictive Analytics

Blog about data science, data mining, predictive analytics, statistical analysis, and the R programming language by Ian Johnson. Silicon Valley, CA

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Data Science, Data Mining and Predictive Analytics | blog.alpha-analysis.com Reviews
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Blog about data science, data mining, predictive analytics, statistical analysis, and the R programming language by Ian Johnson. Silicon Valley, CA
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Data Science, Data Mining and Predictive Analytics | blog.alpha-analysis.com Reviews

https://blog.alpha-analysis.com

Blog about data science, data mining, predictive analytics, statistical analysis, and the R programming language by Ian Johnson. Silicon Valley, CA

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1

Data Science, Data Mining and Predictive Analytics: Regression / Time Series BP Stock Model

http://blog.alpha-analysis.com/2010/06/regression-time-series-bp-stock-model.html

Data Science, Data Mining and Predictive Analytics. Silicon Valley area, CA. Regression / Time Series BP Stock Model. The date of the oil spill. In the Gulf of Mexico was April 20, 2010. British Petroleum stock. Below is an ANOVA table of a regression between change in price as a dependent variable and change in volume as an independent variable. The negative sign for change in volume indicates as volume increases, BP stock has declined over this time period and is statistically significant. For only loo...

2

Data Science, Data Mining and Predictive Analytics: May 2015

http://blog.alpha-analysis.com/2015_05_01_archive.html

Data Science, Data Mining and Predictive Analytics. Silicon Valley area, CA. R Text Mining: The Wells Report. Word Cloud Wells Report. Story: Patriots Deflated Footballs. Document to be text mined: Wells Report. How to Create Word Cloud using R:. Tm: Text Mining Package. 1) Convert PDF to text file using pdftotext. 2) Clean the document and remove numbers, punctuation, symbols, and stop words. A[ 1] - gsub( "psig" , "psi" , a[ 1] ) a - tm map(a, PlainTextDocument) #neccessary after word replacement.

3

Data Science, Data Mining and Predictive Analytics: January 2012

http://blog.alpha-analysis.com/2012_01_01_archive.html

Data Science, Data Mining and Predictive Analytics. Silicon Valley area, CA. Three Card Poker Game for R. A few years ago I created a comprehensive simulation of the card game three card poker for a client in Las Vegas. I recently converted the simulation into a simple command line game for R. Three Card Poker Game for R (Linux). Three Card Poker Game for R (Windows). Posted by Ian Johnson. Subscribe to: Posts (Atom). Silicon Valley, CA, United States. View my complete profile. Three Card Poker Game for R.

4

Data Science, Data Mining and Predictive Analytics: Best Statistical Software Package

http://blog.alpha-analysis.com/2010/05/best-statistical-software-package.html

Data Science, Data Mining and Predictive Analytics. Silicon Valley area, CA. Best Statistical Software Package. The best statistical software package is the tool that works best for the user based upon what needs to be done, cost, and what works best with existing software. Similar to using a particular tool, each package has its advantages and disadvantages over each other. The major packages I use are R, SPSS, and SAS. Using iteratively reweighted least squares (IRLS). The best way to run R. Runs on Wi...

5

Data Science, Data Mining and Predictive Analytics: R Text Mining: The Wells Report

http://blog.alpha-analysis.com/2015/05/text-mining-wells-report-using-r.html

Data Science, Data Mining and Predictive Analytics. Silicon Valley area, CA. R Text Mining: The Wells Report. Word Cloud Wells Report. Story: Patriots Deflated Footballs. Document to be text mined: Wells Report. How to Create Word Cloud using R:. Tm: Text Mining Package. 1) Convert PDF to text file using pdftotext. 2) Clean the document and remove numbers, punctuation, symbols, and stop words. A[ 1] - gsub( "psig" , "psi" , a[ 1] ) a - tm map(a, PlainTextDocument) #neccessary after word replacement.

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Factor Evaluation in Quantitative Portfolio Management « The R Trader

http://www.thertrader.com/2015/03/23/factor-evaluation-in-quantitative-portfolio-management

The R Trader Blog. Risk as a “Survival Variable”. R financial time series tips everyone should know about ». Factor Evaluation in Quantitative Portfolio Management. March 23, 2015. When it comes to managing a portfolio of stocks versus a benchmark the problem is very different from defining an absolute return strategy. In the former one has to hold more stocks than in the later where no stocks at all can be held if there is not good enough opportunity. The reason for that is the tracking error. Between t...

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Book Review « The R Trader

http://www.thertrader.com/category/book-review

The R Trader Blog. Archive for the 'Book Review' Category. Introduction to R for Quantitative Finance – Book Review. January 10, 2014. I used some spare time I had over the christmas break to review a book I came across: Introduction to R for Quantitative Finance. An introduction to the book by the authors can be found here. Chap 1: Time Series Analysis. Chap 2: Portfolio Optimisation. Chap 3: Asset Pricing Model. Chap 4: Fixed Income Securities. Chap 5: Estimating the Term Structure of Interest Rates.

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Wakefield: Random Data Set (Part II) | TRinker's R Blog

https://trinkerrstuff.wordpress.com/2015/04/30/wakefield-random-data-set-part-ii

TRinker's R Blog. Experiments and Experiences in R. Random Data Sets Quickly. Cracking Safe Cracker with R →. Wakefield: Random Data Set (Part II). April 30, 2015. This post is part II of a series detailing the GitHub package, wakefield. For generating random data sets. The First Post (part I). Was a test run to gauge user interest. I received positive feedback and some ideas for improvements, which I’ll share below. The post is broken into the following sections:. Dummy Coding Expansion of Factors.

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About « The R Trader

http://www.thertrader.com/about

The R Trader Blog. I have been in the Quantitative Trading/Investment industry for more than 15 years, developing, testing and trading all sorts of investment strategies on all major asset classes. I started this blog to discuss the use of R in the context of systematic investment strategies. I also provide consulting services for high net worth individuals and institutions on all topics related to this blog which entails but is not limited to:. Quantitative evaluation of investment/trading strategies.

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R financial time series tips everyone should know about « The R Trader

http://www.thertrader.com/2015/07/07/r-financial-time-series-tips-everyone-should-know-about

The R Trader Blog. Factor Evaluation in Quantitative Portfolio Management. The Rise of the Robots (Advisors…) ». R financial time series tips everyone should know about. July 7, 2015. The xts package is the must have when it comes to times series in R. The example below loads the package and creates a daily time series of 400 days normaly distributed returns. Library(xts) myTs - xts(rnorm(400)/100,order.by=seq(Sys.Date()-399,Sys.Date(),days). It determines how the binding is done. NewTs - allMyTs[endpoin...

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reports | TRinker's R Blog

https://trinkerrstuff.wordpress.com/my-r-packages/reports

TRinker's R Blog. Experiments and Experiences in R. Reports is a package that assists in writing reports and presentations by providing a frame work that brings together existing R, LaTeX/.docx and Pandoc tools. The package is designed to be used with RStudio. The user will want to download these free programs to maximize the effectiveness of the reports package. To download the development version of reports:. Download the zip ball. On it, or use the devtools. Package to install the development version:.

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My R Packages | TRinker's R Blog

https://trinkerrstuff.wordpress.com/my-r-packages

TRinker's R Blog. Experiments and Experiences in R. I have developed multiple packages on CRAN. Leave a Reply Cancel reply. Enter your comment here. Fill in your details below or click an icon to log in:. Address never made public). You are commenting using your WordPress.com account. ( Log Out. You are commenting using your Twitter account. ( Log Out. You are commenting using your Facebook account. ( Log Out. You are commenting using your Google account. ( Log Out. Notify me of new comments via email.

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tylerrinker | TRinker's R Blog

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TRinker's R Blog. Experiments and Experiences in R. I am Literacy PhD student with a bent for the quantitative and a passion for R. Googleformr at Work: Pneumatic Road Tube Allegory. May 12, 2016. Steve Simpson (@data steve) created the googleformr package to enable users to easily send information to a Google Form. It’s a nice way to send and securely store data via R and the price is great…FREE! A Pneumatic Road Tube Allegory…Kinda … Continue reading →. Pacman Ver 0.4.1 Release. March 31, 2016. My wife...

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qdapRegex | TRinker's R Blog

https://trinkerrstuff.wordpress.com/my-r-packages/qdapregex

TRinker's R Blog. Experiments and Experiences in R. Is a collection of regular expression tools associated with the qdap package. That may be useful outside of the context of discourse analysis. Tools include removal/extraction/replacement of abbreviations, dates, dollar amounts, email addresses, hash tags, numbers, percentages, person tags, phone numbers, times, and zip codes. To download the development version of qdapRegex:. Download the zip ball. On it, or use the devtools. Windows users need Rtools.

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Cracking Safe Cracker with R | TRinker's R Blog

https://trinkerrstuff.wordpress.com/2015/05/30/1646

TRinker's R Blog. Experiments and Experiences in R. Wakefield: Random Data Set (Part II). How do I re-arrange? Ordering a plot re-revisited →. Cracking Safe Cracker with R. May 30, 2015. My wife got me a Safe Cracker 40. Possible combinations. I think it’s best to understand the logic by watching the video:. Here are the dials. The NA. This is a brute force method but is still pretty quick. I made a shift function to treat vectors like circles or in this case dials. Here’s a demo of shift. Isna(c4b)] - n...

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Data Science, Data Mining and Predictive Analytics

Data Science, Data Mining and Predictive Analytics. Silicon Valley area, CA. R: K-Means Clustering MLB Data. Is a useful unsupervised learning data mining tool for assigning n. Groups which allows a practitioner to segment a dataset. I play in a fantasy baseball league and using five offensive variables (R, AVG, HR, RBI, SB) I am going to use k. 1) Determine how many. There are in major league baseball. Is there a power and high average group? Is there a low power, high average, and speed group? Players ...

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