Market Filter Back Test Shiny web application

February 15, 2013
By
Market Filter Back Test Shiny web application

Today, I want to share the Market Filter Back Test application (code at GitHub). This is the forth application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make back-tests, and create summary reports. The motivation for this series

Read more »

Video: Data Mining with R

February 15, 2013
By

Yesterday's Introduction to R for Data Mining webinar was a record setter, with more than 2000 registrants and more than 700 attending the live session presented by Joe Rickert. If you missed it, I've embedded the video replay below, and Joe's slides (with links to many useful resources) are also available. During the webinar, Joe demoed several examples of...

Read more »

Incorporating Preference Construction into the Choice Modeling Process

February 15, 2013
By

Statistical modeling often begins with the response generation process because data analysis is a combination of mathematics and substantive theory.  It is a theory of how things work that determines how we ought to collect and analyze&n...

Read more »

Clustering Loss Development Factors

February 15, 2013
By
Clustering Loss Development Factors

  Anytime I get a new hammer, I waste no time in trying to find something to bash with it. Prior to last year, I wouldn’t have known what a cluster was, other than the first half of a slang term used to describe a poor decision-making process. Now I’ve seen it in action a

Read more »

Zurich, Feb 2013 – Basic R Course

February 15, 2013
By

(This article was first published on Rmetrics blogs, and kindly contributed to R-bloggers) To leave a comment for the author, please follow the link and comment on their blog: Rmetrics blogs. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave,...

Read more »

New Data Scientist role at Lloyd’s

February 15, 2013
By
New Data Scientist role at Lloyd’s

Lloyd's of London is looking for a Data Scientist as part of the Analysis team. See Lloyd's career web site for more details.

Read more »

FillIn: a function for filling in missing data in one data frame with info from another

February 15, 2013
By

Sometimes I want to use R to fill in values that are missing in one data frame with values from another. For example, I have data from the World Bank on government deficits. However, there are some country-years with missing data. I gathered data from ...

Read more »

Sorting rows and colums in a matrix (with some music, and some magic)

February 14, 2013
By
Sorting rows and colums in a matrix (with some music, and some magic)

This morning, I was working on some paper on inequality measures, and for computational reasons, I had to sort elements in a matrix. To make it simple, I had a rectangular matrix, like the one below, > set.seed(1) > u=sample(1:(nc*nl)) > (M1=matrix(u,nl,nc)) 7 5 11 23 6 17 9 18 1 21...

Read more »

January Seasonality Shiny web application

February 14, 2013
By
January Seasonality Shiny web application

Today, I want to share the January Seasonality application (code at GitHub). This example is based on the An Example of Seasonality Analysis post. This is the third application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make

Read more »

Make a Valentine’s Heart with R

February 14, 2013
By
Make a Valentine’s Heart with R

If you haven't sent your loved one a Valentine's Day greeting yet, it's not too late! Thanks to Guillermo Santos who pointed out an R script from Berkeley's Concepts in Computing with Data course, I created the following Valentine's Day card for my husband: If you want to make one for your loved one, you can use the R...

Read more »

GPS Basemaps in R Using get_map

February 14, 2013
By
GPS Basemaps in R Using get_map

There are many different maps you can use for a background map for your gps or other latitude/longitude data (i.e. any time you're using geom_path, geom_segment, or geom_point.)get_mapHelpfully, there's just one function that will allow you to query Google Maps, OpenStreetMap, Stamen maps, or CloudMade maps: get_map in the ggmap package. You could also use either get_googlemap, get_openstreetmap, get_stamenmap, or get_cloudmademap, but...

Read more »

Major update to the R-package geomorph

February 14, 2013
By

Hi Folks,We have just completed a major update to the R-package geomorph: software for geometric morphometric analyses in R.  Included are several new functions to  carry out additional GM analyses, as well as enhancements of existing functio...

Read more »

Veterinary Epidemiologic Research: Linear Regression

February 14, 2013
By
Veterinary Epidemiologic Research: Linear Regression

This post will describe linear regression as from the book Veterinary Epidemiologic Research, describing the examples provided with R. Regression analysis is used for modeling the relationship between a single variable Y (the outcome, or dependent variable) measured on a continuous or near-continuous scale and one or more predictor (independent or explanatory variable), X. If

Read more »

Happy Valentine’s Day @mrshrbrmstr!

February 14, 2013
By
Happy Valentine’s Day @mrshrbrmstr!

dat<- data.frame(t=seq(0, 2*pi, by=0.1) ) xhrt <- function(t) 16*sin(t)^3 yhrt <- function(t) 13*cos(t)-5*cos(2*t)-2*cos(3*t)-cos(4*t) dat$y=yhrt(dat$t) dat$x=xhrt(dat$t) with(dat, polygon(x,y, col="hotpink")) i heaRt you! (R code inspired by/lifted from: DWin on StackOverflow)

Read more »

Population simulation leads to Valentine’s Day a[R]t

February 14, 2013
By
Population simulation leads to Valentine’s Day a[R]t

Working on a quick-and-dirty simulation of people wandering around until they find neighbors, then settling down. After playing with the coloring a bit I arrived at the above image, which I quite like. Code below: # Code by Matt Asher for statisticsblog.com # Feel free to modify and redistribute, but please keep this notice  

Read more »

R database interfaces

February 14, 2013
By

Several packages on CRAN provide (or relate to) interfaces between databases and R.  Here is a summary, mostly in the words of the package descriptions.  Remember that package names are case-sensitive. The packages that talk about being DBI-compliant are referring to the DBI package (see below in “Other SQL”). MySQL dbConnect: Provides a graphical user The post R...

Read more »

Getting a simple tree via NCBI

February 14, 2013
By
Getting a simple tree via NCBI

I was just at the Phylotastic hackathon in Tucson, AZ at the iPlant facilities at the UofA. A problem that needs to be solved is getting the incrasingly vast phylogenetic information to folks not comfortable building their own phylogenies. Phylomatic has made this super easy for people that want plant phylogenies (at least 250 or so papers...

Read more »

Getting a simple tree via NCBI

February 14, 2013
By
Getting a simple tree via NCBI

I was just at the Phylotastic hackathon in Tucson, AZ at the iPlant facilities at the UofA. A problem that needs to be solved is getting the incrasingly vast phylogenetic information to folks not comfortable building their own phylogenies. Phylomatic has made this super easy for people that want plant phylogenies (at least 250 or so papers...

Read more »

Version 1.0 of multilevelPSA Available on CRAN

February 14, 2013
By
Version 1.0 of multilevelPSA Available on CRAN

Version 1.0 of multilevelPSA has been released to CRAN. The multilevelPSA package provides functions to estimate and visualize propensity score models with multilevel, or clustered, data. The graphics are an extension of PSAgraphics package by Helmreich and Pruzek. The example below will investigate the differences between private and public school internationally using the Programme of International Student Assessment...

Read more »

No Statistical Panacea, Hierarchical or Otherwise

February 13, 2013
By
No Statistical Panacea, Hierarchical or Otherwise

Everyone in academia knows how painful the peer-review publication process can be. It’s a lot like Democracy, in that it’s the worst system ever invented, except for all the others. The peer-review process does a fair job at promoting good … Continue reading →

Read more »

Apply Yourself !

February 13, 2013
By
Apply Yourself !

Hello. Welcome to my debut post ! Check the About link to see what this Blog intends to accomplish. In this article I discuss a general approach for dealing with the problem of splitting a data frame based on a grouping variable and then doing some more operations per group. A secondary goal is to

Read more »

Multiple Stocks Plot Shiny web application

February 13, 2013
By
Multiple Stocks Plot Shiny web application

Today, I want to share the Multiple Stocks Plot application (code at GitHub). This is the second application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make back-tests, and create summary reports. The motivation for this series of

Read more »

In case you missed it: January 2103 Roundup

February 13, 2013
By

In case you missed them, here are some articles from January of particular interest to R users. Anthony Damico created an amusing and useful flowchart for finding resources for learning R, especially for survey analysis. All R users: please be counted for the 2013 Rexer Data Miner Survey (R was the #1 software reported in the last survey). Relatedly,...

Read more »

Out-of-sample one-step forecasts

February 13, 2013
By

It is common to fit a model using training data, and then to evaluate its performance on a test data set. When the data are time series, it is useful to compute one-step forecasts on the test data. For some reason, this is much more commonly done by people trained in machine learning rather than statistics. If you are...

Read more »

Mason Earles on interfacing R with the Forest Vegetation Simulator

February 13, 2013
By

Mason Earles gave a great presentation this week at Davis R Users’ Group about linking R with the Forest Vegetation Simulator (FVS). FVS is a model developed by the US Forest Service to simulate forest growth over time. It’s written in FORTRAN and has been around since the 1970s. FVS has recently gone open-source (its...

Read more »

Parallel execution of randomForestSRC

February 13, 2013
By
Parallel execution of randomForestSRC

I guess I’m the resident expert on resampling methods at work. I’ve been using bagged predictors and random forests for a while, and have recently been using the randomForestSRC (RF-SRC) package in R (http://cran.r-project.org/web/packages/randomForestSRC). This package merges the two randomForest… Continue reading →

Read more »

Large claims, and ratemaking

February 13, 2013
By
Large claims, and ratemaking

During the course, we have seen that it is natural to assume that not only the individual claims frequency can be explained by some covariates, but individual costs too. Of course, appropriate families should be considered to model the distribution of the cost , given some covariates .Here is the dataset we’ll use, > sinistre=read.table("http://freakonometrics.free.fr/sinistreACT2040.txt", + header=TRUE,sep=";") > sinistres=sinistre...

Read more »

A Shiny example – SAP HANA, R and Shiny

February 13, 2013
By
A Shiny example – SAP HANA, R and Shiny

As you may already know...I love R...a fancy, open source statistics programming language. So today, I decided to learn something new using R.There aren't much Web Servers for R, but there's one that I really like called Rook, that I covered on my blog...

Read more »

igraph degree distribution: count elements

February 13, 2013
By

Unfortunately, the degree.distribution() function of the igraph library returns the intensities of the distribution:> g > plot(g) > summary(g)IGRAPH U--- 10 10 -- Ring graphattr: name (g/c), mutual (g/x), circular (g/x) So instead of having the number of elements, the density/intensities value is returned:> degree.distribution(g) 0 0 1 You can easily verify this in the source code...

Read more »

Sponsors