Forecast Combination in R – slides
The useR! 2019 held in Toulouse ended couple of days ago. I spoke of the recent R journal publication about forecast combinations (joint work with Christoph Weiss and Gernot Roetzer). Slides for the...
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Robust Moving Average
Moving average is one of the most commonly used smoothing method, basically the go-to. It helps us detect trend in the data by smoothing out short term fluctuations. The computation is trivial: take...
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Understanding Variance Explained in PCA
Principal component analysis (PCA) is one of the earliest multivariate techniques. Yet not only it survived but it is arguably the most common way of reducing the dimension of multivariate data, with...
View ArticleForecast Combination talk
Courtesy of R Consortium, you can view my forecast combination talk (16 mins) given in France few months ago, below. The slides for talk and the paper it’s based on can be found here Related posts:...
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CUR matrix decomposition for improved data analysis
I have recently been reading about more modern ways to decompose a matrix. Singular value decomposition is a popular way, but there are more. I went down the rabbit whole. After a couple of “see...
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Most popular posts – 2019
As every year, I checked my analytics so that I can let you know what was popular. This year I have also experimented with a survey where I asked one question at the end of each relevant post. About...
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Understanding Pointwise Mutual Information in Statistics
Intro The term mutual information is drawn from the field of information theory. Information theory is busy with the quantification of information. For example, a central concept in this field is...
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R tips and tricks – Paste a plot from R to a word file
In this post you will learn how to properly paste an R plot\chart\image to a word file. There are few typical problems that occur when people try to do that. Below you can find a simple, clean and...
View ArticleCurse of Dimensionality part 4: Distance Metrics
Many machine learning algorithms rely on distances between data points as their input, sometimes the only input, especially so for clustering and ranking algorithms. The celebrated k-nearest neighbors...
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Machine learning is simply statistics – part 2
Another opinion piece. If you can’t explain it simply you don’t understand it well enough. (Albert Einstein) A bit on Deep Learning What is so deep about deep learning? Nothing. There is nothing deep...
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R tips and tricks – utilities
As the title reads, few more R-related tips and tricks. I hope you have not seen those before. Some utilities Methods are functions which are specifically written for particular class. In the post Show...
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R tips and tricks, on-screen colors
I like using for many reasons. Two of those are (1) easy integration with almost whichever software you can think of, and (2) for its graphical powers. Color-wise, I dare to assume you probably...
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R + Python = Rython
Enough! Enough with that pointless R versus Python debate. I find it almost as pointless as the Bayesian vs Frequentist “dispute”. I advocate here what I advocated there (“..don’t be a Bayesian, nor be...
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Boundary corrected kernel density
Density estimation is now a trivial one-liner script in all modern software. What is not so easy is to become comfortable with the result, how well is is my density estimated? we rarely know. One...
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Understanding Spectral Clustering
Some problems are linear, but some problems are non-linear. I presume that you started your education discussing and solving linear problems which is a natural starting point. For non-linear problems...
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Correlation and correlation structure (4) – asymmetric correlations of equity...
Here I share a refreshing idea from the paper “Asymmetric correlations of equity portfolios” which was published in the Journal of financial Economics, a top tier journal in this field. The question is...
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Why complex models are data-hungry?
If you regularly read this blog then you know I am not one to jump on the “AI Bandwagon”, being quickly weary of anyone flashing the “It’s Artificial Intelligence” joker card. Don’t get me wrong, I...
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Most popular posts – 2020
Littered with Corona, this year was not easy. But looking around me, I feel grateful. The following quote by Socrates comes to mind: “If all our misfortunes were laid in one common heap whence everyone...
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R tips and tricks – Timing and profiling code
Modern statistical methods use simulations; generating different scenarios and repeating those thousands of times over. Therefore, even trivial operations burden computational speed. In the words of my...
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Understanding Variance Explained in PCA – Matrix Approximation
Principal component analysis (PCA from here on) is performed via linear algebra functions called eigen decomposition or singular value decomposition. Since you are actually reading this, you may well...
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