# Posts by Tags

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## Compiling TensorFlow on Arch Linux

Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA

## Handcoding a Difference in Differences

In this post we will discuss how to manually implement a Difference-in-Differences (DiD) estimator in R, using simulated data.

## sigmoid package

The sigmoid package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples.

## Handcoding a Recurrent Neural Network

This is an example of how to build a Recurrent Neural Network in R.

## Handcoding a Logit Model

Below is an example of how to handcode a logit model.

## Handcoding a Difference in Differences

In this post we will discuss how to manually implement a Difference-in-Differences (DiD) estimator in R, using simulated data.

## Handcoding a Panel Model

The most basic panel estimation is the Pooled OLS model, this model combines all data across indices and performs a regular Ordinary Least Squares Estimation.

## Neural Network IV with Simulated Data

Some simulated data, borrowed from this post.

A simple example

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## learNN package

The learNN package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples....

## Linear Model and Neural Network

In this short post I want to quickly demonstrate how the most basic neural network (no hidden layer) gives us the same results as the linear model.

## Hand Coding the Power of a Test

We want to test if our population average is different from twenty.

## WIOD data sets package

The wiod package is now available on CRAN. The package contains the complete WIOD data sets, in a format compatible with the decompr and gvc package.

## Hand Coding Categorical Variables

In last week’s posts we discussed handcoding a linear model and writing a convenient function for this, in today’s post we will take this a step further by i...

## Hand Coding a Linear Model function

In yesterday’s post we developed a method for constructing a multivariate linear model with an intercept.

## Hand Coding the Linear Model

In order to understand statistics, you have to do the calculations yourself!

## introducing diagonals

A new R package diagonals is now available on CRAN. The package implements several tools for dealing with fat diagonals on matrices, such as this one:

## plot.ly

Quick experiment on embedding plot.ly graphics.

## diagonals in a network

A typical example in which diagonals can be helpful is Social Network Analysis. For example, if we use matrices to represent friendship perceptions between i...

## gvc package on CRAN

A new R package gvc is now available on CRAN. The package implements several global value chain indicators

## decompr on CRAN

I am proud to announce that after a few emails back and forth with Prof. Brian Ripley, which consisted mostly of me appologising for not following the proper...

## Data Science Specialisation

Yesterday the Johns Hopkins School of Public Health published a post about their Data Science Specialisation on the online MOOC platform Coursera.

## Learning R and Git

In yesterday’s post I discussed some of the principles I use to make my work replicable and - to an extent - reproducible. In this post I want to collect som...

## The decompr package

I am proud to announce the beta version of the decompr R package. The package implements Export Decomposition using the Wang-Wei-Zhu (Wang, Wei, and Zhu 2013...

## ggvis, shiny, and HTML5 slides

ggvis is wonderful new tool to create interactive graphics, which was build with Shiny apps in mind. In this post I will go over how you can create a Shiny a...

## Handcoding a Recurrent Neural Network

This is an example of how to build a Recurrent Neural Network in R.

## Compiling TensorFlow on Arch Linux

Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA

## Promoting Content in Africa

In the keynote at African Peering Forum (AfPIF) 2016 I presented the Promoting Content in Africa report written together with Michael Kende, these are the...

## Male/Female Bargaining Power and Child Growth

Increased male bargaining power in households causes greater expenditure on food, an improvement in Weight-for-Age Z-scores in young children, and a deterior...

## Hand Coding Categorical Variables

In last week’s posts we discussed handcoding a linear model and writing a convenient function for this, in today’s post we will take this a step further by i...

## Male/Female Bargaining Power and Child Growth

Increased male bargaining power in households causes greater expenditure on food, an improvement in Weight-for-Age Z-scores in young children, and a deterior...

## gvc package on CRAN

A new R package gvc is now available on CRAN. The package implements several global value chain indicators

## decompr on CRAN

I am proud to announce that after a few emails back and forth with Prof. Brian Ripley, which consisted mostly of me appologising for not following the proper...

## Data Science Specialisation

Yesterday the Johns Hopkins School of Public Health published a post about their Data Science Specialisation on the online MOOC platform Coursera.

## WIOD data sets package

The wiod package is now available on CRAN. The package contains the complete WIOD data sets, in a format compatible with the decompr and gvc package.

## gvc package on CRAN

A new R package gvc is now available on CRAN. The package implements several global value chain indicators

## decompr on CRAN

I am proud to announce that after a few emails back and forth with Prof. Brian Ripley, which consisted mostly of me appologising for not following the proper...

## The decompr package

I am proud to announce the beta version of the decompr R package. The package implements Export Decomposition using the Wang-Wei-Zhu (Wang, Wei, and Zhu 2013...

## Compiling TensorFlow on Arch Linux

Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA

## introducing diagonals

A new R package diagonals is now available on CRAN. The package implements several tools for dealing with fat diagonals on matrices, such as this one:

## diagonals in a network

A typical example in which diagonals can be helpful is Social Network Analysis. For example, if we use matrices to represent friendship perceptions between i...

## learNN package

The learNN package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples....

## Hand Coding Categorical Variables

In last week’s posts we discussed handcoding a linear model and writing a convenient function for this, in today’s post we will take this a step further by i...

## Learning R and Git

In yesterday’s post I discussed some of the principles I use to make my work replicable and - to an extent - reproducible. In this post I want to collect som...

## Hand Coding a Linear Model function

In yesterday’s post we developed a method for constructing a multivariate linear model with an intercept.

## ggvis, shiny, and HTML5 slides

ggvis is wonderful new tool to create interactive graphics, which was build with Shiny apps in mind. In this post I will go over how you can create a Shiny a...

## WIOD data sets package

The wiod package is now available on CRAN. The package contains the complete WIOD data sets, in a format compatible with the decompr and gvc package.

## gvc package on CRAN

A new R package gvc is now available on CRAN. The package implements several global value chain indicators

## decompr on CRAN

I am proud to announce that after a few emails back and forth with Prof. Brian Ripley, which consisted mostly of me appologising for not following the proper...

## The decompr package

I am proud to announce the beta version of the decompr R package. The package implements Export Decomposition using the Wang-Wei-Zhu (Wang, Wei, and Zhu 2013...

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## Hand Coding the Power of a Test

We want to test if our population average is different from twenty.

## Hand Coding the Linear Model

In order to understand statistics, you have to do the calculations yourself!

## learNN package

The learNN package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples....

## ggvis, shiny, and HTML5 slides

ggvis is wonderful new tool to create interactive graphics, which was build with Shiny apps in mind. In this post I will go over how you can create a Shiny a...

## Hand Coding the Power of a Test

We want to test if our population average is different from twenty.

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## Promoting Content in Africa

In the keynote at African Peering Forum (AfPIF) 2016 I presented the Promoting Content in Africa report written together with Michael Kende, these are the...

## Making the Next Billion Demand Access

The Local-Content Effect of google.co.za in Setswana

## Making the Next Billion Demand Access

The Local-Content Effect of google.co.za in Setswana

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## Learning R and Git

In yesterday’s post I discussed some of the principles I use to make my work replicable and - to an extent - reproducible. In this post I want to collect som...

## Handcoding a Difference in Differences

In this post we will discuss how to manually implement a Difference-in-Differences (DiD) estimator in R, using simulated data.

## Handcoding a Panel Model

The most basic panel estimation is the Pooled OLS model, this model combines all data across indices and performs a regular Ordinary Least Squares Estimation.

## Neural Network IV with Simulated Data

Some simulated data, borrowed from this post.

A simple example

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## Linear Model and Neural Network

In this short post I want to quickly demonstrate how the most basic neural network (no hidden layer) gives us the same results as the linear model.

## Hand Coding the Power of a Test

We want to test if our population average is different from twenty.

## Hand Coding Categorical Variables

In last week’s posts we discussed handcoding a linear model and writing a convenient function for this, in today’s post we will take this a step further by i...

## Hand Coding a Linear Model function

In yesterday’s post we developed a method for constructing a multivariate linear model with an intercept.

## Hand Coding the Linear Model

In order to understand statistics, you have to do the calculations yourself!

## Hand Coding Instumental Variables

In a previous post we discussed the linear model and how to write a function that performs a linear regression. In this post we will use that linear model fu...

## Hand Coding Categorical Variables

In last week’s posts we discussed handcoding a linear model and writing a convenient function for this, in today’s post we will take this a step further by i...

## Hand Coding a Linear Model function

In yesterday’s post we developed a method for constructing a multivariate linear model with an intercept.

## Hand Coding the Linear Model

In order to understand statistics, you have to do the calculations yourself!

## Promoting Content in Africa

In the keynote at African Peering Forum (AfPIF) 2016 I presented the Promoting Content in Africa report written together with Michael Kende, these are the...

## Handcoding a Logit Model

Below is an example of how to handcode a logit model.

## Backpropagation: the simplest form

doing backpropagation using pen and paper

A simple example

## learNN package

The learNN package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples....

## Linear Model and Neural Network

In this short post I want to quickly demonstrate how the most basic neural network (no hidden layer) gives us the same results as the linear model.

## introducing diagonals

A new R package diagonals is now available on CRAN. The package implements several tools for dealing with fat diagonals on matrices, such as this one:

## Data Science Specialisation

Yesterday the Johns Hopkins School of Public Health published a post about their Data Science Specialisation on the online MOOC platform Coursera.

## diagonals in a network

A typical example in which diagonals can be helpful is Social Network Analysis. For example, if we use matrices to represent friendship perceptions between i...

## Backpropagation: the simplest form

doing backpropagation using pen and paper

Development

## sigmoid package

The sigmoid package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples.

## Neural Network IV with Simulated Data

Some simulated data, borrowed from this post.

A simple example

## learNN package

The learNN package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples....

## Linear Model and Neural Network

In this short post I want to quickly demonstrate how the most basic neural network (no hidden layer) gives us the same results as the linear model.

## Hand Coding Categorical Variables

In last week’s posts we discussed handcoding a linear model and writing a convenient function for this, in today’s post we will take this a step further by i...

## Hand Coding a Linear Model function

In yesterday’s post we developed a method for constructing a multivariate linear model with an intercept.

## Hand Coding the Linear Model

In order to understand statistics, you have to do the calculations yourself!

## introducing diagonals

A new R package diagonals is now available on CRAN. The package implements several tools for dealing with fat diagonals on matrices, such as this one:

## gvc package on CRAN

A new R package gvc is now available on CRAN. The package implements several global value chain indicators

## decompr on CRAN

I am proud to announce that after a few emails back and forth with Prof. Brian Ripley, which consisted mostly of me appologising for not following the proper...

## The decompr package

I am proud to announce the beta version of the decompr R package. The package implements Export Decomposition using the Wang-Wei-Zhu (Wang, Wei, and Zhu 2013...

## Handcoding a Difference in Differences

In this post we will discuss how to manually implement a Difference-in-Differences (DiD) estimator in R, using simulated data.

## Handcoding a Panel Model

The most basic panel estimation is the Pooled OLS model, this model combines all data across indices and performs a regular Ordinary Least Squares Estimation.

## Handcoding a Difference in Differences

In this post we will discuss how to manually implement a Difference-in-Differences (DiD) estimator in R, using simulated data.

## Handcoding a Panel Model

The most basic panel estimation is the Pooled OLS model, this model combines all data across indices and performs a regular Ordinary Least Squares Estimation.

## plot.ly

Quick experiment on embedding plot.ly graphics.

## Hand Coding the Power of a Test

We want to test if our population average is different from twenty.

## Hand Coding a Linear Model function

In yesterday’s post we developed a method for constructing a multivariate linear model with an intercept.

## Promoting Content in Africa

In the keynote at African Peering Forum (AfPIF) 2016 I presented the Promoting Content in Africa report written together with Michael Kende, these are the...

## Handcoding a Recurrent Neural Network

This is an example of how to build a Recurrent Neural Network in R.

## ggvis, shiny, and HTML5 slides

ggvis is wonderful new tool to create interactive graphics, which was build with Shiny apps in mind. In this post I will go over how you can create a Shiny a...

## sigmoid package

The sigmoid package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples.

## ggvis, shiny, and HTML5 slides

ggvis is wonderful new tool to create interactive graphics, which was build with Shiny apps in mind. In this post I will go over how you can create a Shiny a...

## diagonals in a network

A typical example in which diagonals can be helpful is Social Network Analysis. For example, if we use matrices to represent friendship perceptions between i...

## Hand Coding the Power of a Test

We want to test if our population average is different from twenty.