# Posts Tagged ‘ R ’

## abcfr 0.9-3

August 26, 2015
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In conjunction with our reliable ABC model choice via random forest paper, about to be resubmitted to Bioinformatics, we have contributed an R package called abcrf that produces a most likely model and its posterior probability out of an ABC reference table. In conjunction with the realisation that we could devise an approximation to the […]

## Visualising the predictive distribution of a log-transformed linear model

August 25, 2015
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Last week I presented visualisations of theoretical distributions that predict ice cream sales statistics based on linear and generalised linear models, which I introduced in an earlier post.Theoretical distributionsToday I will take a closer look at t...

## Data frames and tables in Scala

August 21, 2015
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Introduction To statisticians and data scientists used to working in R, the concept of a data frame is one of the most natural and basic starting points for statistical computing and data analysis. It always surprises me that data frames aren’t a core concept in most programming languages’ standard libraries, since they are essentially a … Continue reading Data frames and tables in Scala

## Kickin’ it with elastic net regression

August 20, 2015
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With the kind of data that I usually work with, overfitting regression models can be a huge problem if I'm not careful. Ridge regression is a really effective technique for thwarting overfitting. It does this by penalizing the L2 norm… Continue reading →

## Display of Geographic Data in R

August 18, 2015
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This was a deck used in my presentation to the Inland Northwest R user Group this past Friday (August 14, 2015). It relies on the work done by many folks, including Ari Lamstein, Kyle Walker, Erik Erhardt, and the kind folks at R-Studio. Please click o...

## Visualising theoretical distributions of GLMs

August 18, 2015
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Two weeks ago I discussed various linear and generalised linear models in R using ice cream sales statistics. The data showed not surprisingly that more ice cream was sold at higher temperatures.icecream

## R, Python, and SAS: Getting Started with Linear Regression

August 17, 2015
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Consider the linear regression model, $$y_i=f_i(\boldsymbol{x}|\boldsymbol{\beta})+\varepsilon_i,$$ where $y_i$ is the response or the dependent variable at the $i$th case, $i=1,\cdots, N$ and the predictor or the independent variable is the $\boldsymbol{x}$ term defined in the mean function $f_i(\boldsymbol{x}|\boldsymbol{\beta})$. For simplicity, consider the following simple linear regression (SLR) model, $$y_i=\beta_0+\beta_1x_i+\varepsilon_i.$$ To obtain the (best) estimate of $\beta_0$ and $\beta_1$, we solve for the least residual sum of…

## Seattle histogram

August 16, 2015
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Filed under: pictures, R, Statistics, Travel Tagged: histogram, sculpture, Seattle, Washington Convention Center

## The Rise of the Robots (Advisors…)

August 15, 2015
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The Asset Management industry is on the verge of a major change. Over the last couple of years Robots Advisors (RA) have emerged as new players. The term itself is hard to define as it encompasses a large variety of services. Some are designed to help traditional advisers to better allocate their clients money and some are […]

## Calling R from Scala sbt projects using rscala

August 15, 2015
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Overview In the previous post I showed how the rscala package (which has replaced the jvmr package) can be used to call Scala code from within R. In this post I will show how to call R from Scala code. I have previously described how to do this using jvmr. This post is really just … Continue reading Calling R from Scala sbt projects using rscala