mathewanalytics.com
R | Mathew Analytics
https://mathewanalytics.com/category/r
Introduction to the RMS Package. February 5, 2017. We start this introduction to the rms package with the datadist function, which computes statistical summaries of predictors to automate estimation and plotting of effects. The user will generally supply the final data frame to the datadist function and set the data distribution using the options function. Note that if you modify the data in your data frame, then you will need to reset the distribution summaries using datadist. This may not seem like any...
mathewanalytics.com
Statistical Reading Rainbow | Mathew Analytics
https://mathewanalytics.com/2016/10/17/statistical-reading-rainbow
October 17, 2016. Statistics in Plain English – Urdan. Clear, concise, and covers all the fundamental items that one would need to know. Everything from descriptive statistics to linear regression are covered, with many good examples. Even if you never use ANOVA or factor analysis, this is a good book to review and one that I strongly recommend to people who are interested in data science. Principles of Statistics – Balmer. Fundamentals of Modern Statistical Methods – Wilcox. While I don’t regularl...
mathewanalytics.com
sql | Mathew Analytics
https://mathewanalytics.com/category/sql
October 11, 2016. I’ve been putting together a basic SQL cheat sheet that could be used as a reference guide. Here are a series of common procedures that should be of use for anyone who uses SQL to extract data. No explanations are provided as they should largely be known to the end user. Turning Data Into Awesome With sqldf and pandasql. June 29, 2015. SELECT COUNT(*) FROM df2 WHERE state = 'CA'") COUNT(*) 1 4 sqldf. 1 David Spade -2.09 TX 2 Joe Montana 1.16 TX sqldf. COUNT(df1.var1) 1 AZ 1 2 CA. 0 Davi...
leftcensored.skepsi.net
Left Censored | Where to begin… | Page 2
http://leftcensored.skepsi.net/page/2
Where to begin…. Newer posts →. The performance cost of a for-loop, and some alternatives. August 21, 2011. I’ve recently been spending a lot of time running various simulations in R. Because I often use snow to perform simulations across several computers/cores, results typically come back in the form of a list object. Summarizing the results from a list is simple enough using a. Family of functions ( R. Is, after all, a functional language. With a large list, particularly when the results from. For met...
leftcensored.skepsi.net
Jason | Left Censored
http://leftcensored.skepsi.net/author/jason
Where to begin…. R and MPI on Ohio Supercomputer Center’s Oakley cluster. February 17, 2015. A few years ago, I wrote a short guide to Using R and snow on the Ohio Supercomputer Center’s Glenn cluster. Several things have changed in the world of R since then (namely, the inclusion of the parallel package into … Continue reading →. Boolean 3 (finally) on CRAN. June 25, 2014. The Latent Path Model for Social Networks: Polmeth 2013 poster. August 31, 2013. Not a good measure of electoral persistence. Pearso...
leftcensored.skepsi.net
Political parties | Left Censored
http://leftcensored.skepsi.net/category/political-parties
Where to begin…. Category Archives: Political parties. Not a good measure of electoral persistence. December 30, 2012. Pearson’s product-moment correlation, (r ), is an incredibly useful tool for getting some idea about how two variables are (linearly) related. But there are times when using Pearson’s (r ) is not appropriate and, even if linearity and all other assumptions hold, … Continue reading →. R and MPI on Ohio Supercomputer Center’s Oakley cluster. Boolean 3 (finally) on CRAN.
leftcensored.skepsi.net
Graphics | Left Censored
http://leftcensored.skepsi.net/category/graphics
Where to begin…. Not a good measure of electoral persistence. December 30, 2012. Pearson’s product-moment correlation, (r ), is an incredibly useful tool for getting some idea about how two variables are (linearly) related. But there are times when using Pearson’s (r ) is not appropriate and, even if linearity and all other assumptions hold, … Continue reading →. A simple frequency plot. April 8, 2011. R and MPI on Ohio Supercomputer Center’s Oakley cluster. Boolean 3 (finally) on CRAN.
thoughtbasket.com
Uncategorized | Thoughtbasket
https://thoughtbasket.com/category/uncategorized
A place to hold my thoughts on various topics. September 23, 2014. So that I can post video of terrible drivers and parkers. Check out the horror of Spruce restaurant and Sysco food delivery here. Bad Driving, Oroweat Edition. April 10, 2013. Double parked in front of a loading zone. This is on a major east-west artery in San Francisco. Skynet’s Strategy: Nuclear War or Contagion? March 25, 2013. What if the Terminator. Was wrong, and Skynet. One way that Skynet can kill us all. January 9, 2013. From eco...
thoughtbasket.com
Business | Thoughtbasket
https://thoughtbasket.com/tag/business
A place to hold my thoughts on various topics. The End of Being Organized. May 17, 2013. Software is getting better and better at helping manage your life. So that you don’t need stay as organized as you used to. In fact, this article. From one tech journalist is even titled stay disorganized. In the abstract, this is a good thing. Why should people have to remember stuff, or spend time organizing their lives, when computers can do it for them? On folder people vs. non-folder people). Thanks to D...Then ...
mathewanalytics.com
statistics | Mathew Analytics
https://mathewanalytics.com/category/statistics-2
Batch Forecasting in R. December 29, 2016. First, let’s create some data. Ddat - data.frame. 2010/01/01"), as.Date. 1) , value1 = abs. 61), 2) , value2 = abs. 61), 2) , value3 = abs. 61), 2) ) head. We want to forecast future values of the three columns. Because we want to save the results of these models into a list, lets begin by creating a list that contains the same number of elements as our data frame. Data) lst - vector. Lst) - lst.names lst. N train=55){ lst.names - c. N train 1): nrow. Est, h=5)$...
SOCIAL ENGAGEMENT