Blog Archives

scheduleR: a web interface to schedule .R & .Rmd scripts

November 18, 2014
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scheduleR: a web interface to schedule .R & .Rmd scripts

scheduleR is an attempt to create an intuitive interface for scheduling R and Rmarkdown scripts. Especially for the latter, I find the lack of a good scheduling, logging and notification tool the reason for why I don’t use Rmarkdown as much as I could for generating business report / dashboards. I’ve built scheduleR’s web interface The post

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simmer 2.0: a performance boost & revised syntax

October 22, 2014
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simmer 2.0: a performance boost & revised syntax

It was very clear that the performance of the first simmer version was lagging behind. The 2.0 release introduces a C++ based engine and comes with a significant performance boost versus the previous version. While the performance can always be further improved I’m currently quite satisfied with it. Future refinement of the code base will The post

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Introducing simmer: Discrete Event Simulation for R

September 3, 2014
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Introducing simmer: Discrete Event Simulation for R

Introduction The simmer package grew out of a personal need for a simple rapid development discrete event simulation (DES) framework. I work in the hospital sector and at times use a DES approach to simulate hospital processes / patient trajectories. DES can give you a quick look at process bottlenecks and test out the impact The post

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Making publicly available data publicly accessible: Belgium’s Hospital Minimal Data

June 13, 2014
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Making publicly available data publicly accessible: Belgium’s Hospital Minimal Data

In current times data is everywhere. The big challenge however is making it not only available, but also accessible to those who need it. An example of this is the Hospital Minimal Data (Belgium). This dataset is openly published by the Federal Public Service for Health, Food Chain Safety & Environment. From a perspective of The post

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Using neural networks for credit scoring: a simple example

July 4, 2013
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Using neural networks for credit scoring: a simple example

Credit scoring is the practice of analysing a persons background and credit application in order to assess the creditworthiness of the person. One can take numerous approaches on analysing this creditworthiness. In the end it basically comes down to first selecting the correct independent variables (e.g. income, age, gender) that lead to a given level of creditworthiness. In...

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Creating a Business Dashboard in R

March 28, 2013
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Creating a Business Dashboard in R

Business dashboards are available in many shapes and sizes. Business dashboards are useful to create an overview of key performance indicators (KPIs) important for the business strategy and/or operations. There are many flavours of dashboard frameworks and apps available, ranging in price from thousands of dollars to open-source implementations. Apparently  Read more »

Creating a Business Dashboard in R

March 28, 2013
By
Creating a Business Dashboard in R

Business dashboards are available in many shapes and sizes. Business dashboards are useful to create an overview of key performance indicators (KPIs) important for the business strategy and/or operations. There are many flavours of dashboard frameworks and apps available, ranging in price from thousands of dollars to open-source implementations. Apparently there are four key elements to a good dashboard: Simple, communicates easily Minimum distractions…it could cause...

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Genetic algorithms: a simple R example

August 1, 2012
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Genetic algorithms: a simple R example

Genetic algorithm is a search heuristic. GAs can generate a vast number of possible model solutions and use these to evolve towards an approximation of the best solution of the model. Hereby it mimics evolution in nature. GA generates a population, the individuals in this population (often called chromosomes) have  Read more »

Genetic algorithms: a simple R example

August 1, 2012
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Genetic algorithms: a simple R example

Genetic algorithm is a search heuristic. GAs can generate a vast number of possible model solutions and use these to evolve towards an approximation of the best solution of the model. Hereby it mimics evolution in nature. GA generates a population, the individuals in this population (often called chromosomes) have a given state. Once the population is generated, the state of these individuals is evaluated...

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Evolution average number of beds per hospital

July 27, 2012
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Evolution average number of beds per hospital

The OECD collects (among a lot of other statistics) information on the number of hospitals and hospital beds per country. These two parameters combined and its evolution over the years could give an indication on whether or not the country’s hospital landscape is evolving towards large medical centers, small scale  Read more »