Monthly Archives: January 2017

7 Interactive Plots from the Pharmaceutical Industry

January 27, 2017
By

Introduction In a recent blog post we introduced 7 Interactive Bioinformatics Plots Made in Python and R. Here I introduced 7 Interactive Plots from the Pharmaceutical Industry using the plotly R package. These plots are essential for any survival analysis study, where there is interest in time-to-events as often seen in the Pharmaceutical industry. For

Read more »

Simulating from a specified seasonal ARIMA model

January 26, 2017
By

From my email today You use an illustration of a seasonal arima model: ARIMA(1,1,1)(1,1,1)4 I would like to simulate data from this process then fit a model… but I am unable to find any information as to how this can be conducted… if I set phi1, Phi1, theta1, and Theta1 it would be reassuring that

Read more »

Doing magic and analyzing seasonal time series with GAM (Generalized Additive Model) in R

January 26, 2017
By
Doing magic and analyzing seasonal time series with GAM (Generalized Additive Model) in R

As I wrote in the previous post, I will continue in describing regression methods, which are suitable for double seasonal (or multi-seasonal) time series. In the previous post about Multiple Linear Regression, I showed how to use “simple” OLS regression method to model double seasonal time series of electricity consumption and use it for accurate forecasting. Interactions...

Read more »

Cards on the table

January 26, 2017
By
Cards on the table

After the last post building on feedback from readers, the blog is back to the regular program of recycling old Github repos. Today’s project was waiting for its turn here and will involve a Catan card game. Nearly a year ago, I played Catan with my ...

Read more »

BiclustGUI 1.1.0

January 26, 2017
By
BiclustGUI 1.1.0

BiBitR enters the fray! Ewoud De Troyer, University of Hasselt (CenStat) Introduction The latest patch of the BiclustGUI includes the implementation of BiBitR, a simple R wrapper which directly calls the original Java code for applying the BiBit algo...

Read more »

Kung Fu R

January 26, 2017
By
Kung Fu R

A great way to hone your skills as a data scientist is to pick a topic you're passionate about, find some data related to it, and analyze the heck out of it. Jim Vallandingham is clearly passionate about old Kung Fu movies — particularly those from the Shaw Brothers Studio — and has used R to analyze data the...

Read more »

Image Compression with Principal Component Analysis

January 26, 2017
By
Image Compression with Principal Component Analysis

Image compression with principal component analysis is a frequently occurring application of the dimension reduction technique. Recall from a previous post that employed singular value decomposition to compress an image, that an image is a matrix of pixels represented by RGB color values. Thus, principal component analysis can be used... The post Image Compression with Principal Component Analysis...

Read more »

New Zealand bank replaces SAS server with R Server

January 26, 2017
By

Heartland Bank, a rapidly growing bank in New Zealand, has adopted a data-driven approach to analyzing risk, evaluating credit lines, and understanding cash flows. But they found their legacy SAS system to be labor-intensive and time consuming when it came to updating financial models, and it was expensive to boot. (Being licensed on a per-user basis, it was available...

Read more »

Multiple Regression (Part 2) – Diagnostics

January 26, 2017
By
Multiple Regression (Part 2) – Diagnostics

Multiple Regression is one of the most widely used methods in statistical modelling. However, despite its many benefits, it is oftentimes used without checking the underlying assumptions. This can lead to results which can be misleading or even completely wrong. Therefore, applying diagnostics to detect any strong violations of the assumptions is important. In the

Read more »

Using CPLEX in R: Installing cplexAPI in Windows 10

January 26, 2017
By
Using CPLEX in R: Installing cplexAPI in Windows 10

I have a very large mixed integer problem to solve.   COIN‘s solver accessed through Rsymphony did a decent job, but had trouble finding feasible solutions.  I had been told that the IBM cplex  solver was the best on the market for mixed integer programming. Installing cplex is a relatively easy task.  The difficulties began when I … Continue...

Read more »

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)