Merging spatial buffers in R
I’m sure there’s a better way out there, but I struggled to find a way to dissolve polygons that touched/overlapped each other (the special case being buffers). For example, using...continue reading.
I’m sure there’s a better way out there, but I struggled to find a way to dissolve polygons that touched/overlapped each other (the special case being buffers). For example, using...continue reading.
Most people know KEGG pathway, but not everyone knows that it costs at least $2000 to subscribe its database. If you want to save the cost a bit, you can...continue reading.
The proposed solution of the riddle from the Riddler discussed here a few weeks ago is rather approximative, in that the distribution of when the n-sample is made of iid...continue reading.
The scatterplot matrix, known acronymically as SPLOM, is a relatively uncommon graphical tool that uses multiple scatterplots to determine the correlation (if any) between a series of variables. These scatterplots...continue reading.
The scatterplot matrix, known acronymically as SPLOM, is a relatively uncommon graphical tool that uses multiple scatterplots to determine the correlation (if any) between a series of variables. These scatterplots...continue reading.
Version 0.9.5.1 of stringdist is on CRAN. The main new feature, with a huge thanks to our awesome new contributor Chris Muir, is that we made it easy to call...continue reading.
In this post, we’ll return to the Kaggle data containing information on Pitchfork music reviews. In a previous post, I used this dataset to cluster music genres. In the current...continue reading.
A guest post by @MaxMaPichler, MSc student in the Group for Theoretical Ecology / UR Artificial neural networks, especially deep neural networks and (deep) convolutions neural networks, have become increasingly popular...continue reading.
A new update of my sjstats-package just arrived at CRAN. This blog post demontrates those functions of the sjstats-package that deal especially with Bayesian models. The update contains some new...continue reading.
Preambule This academic year I am participating in European Doctoral School of Demography. It is a unique one-year-long training for PhD students in demography. It keeps migrating across European research...continue reading.
By Yuri Fonseca Demand models In the previous post about pricing optimization (link here), we discussed a little about linear demand and how to estimate optimal prices in that case....continue reading.
Someday you will find me caught beneath the landslide (Champagne Supernova, Oasis) I recently read a book called Snowflake Seashell Star: Colouring Adventures in Numberland by Alex Bellos and Edmund Harris...continue reading.
Facebook Twitter Google+ LinkedIn If you like magical incantations in Data Science, please welcome the Ceteris Paribus Plots. Otherwise feel free to call them What-If Plots. Ceteris Paribus (latin for...continue reading.
Geocomputation with R: brief history, vector, raster, mapping, R-GIS bridgescontinue reading.
When visualizing a network with nodes that refer to a geographic place, it is often useful to put these nodes … Read More →continue reading.
At Appsilon we frequently build advanced R/Shiny dashboards that need user authentication. I would like to share with you how we implement user management – user accounts, the authorization process...continue reading.
A fun summertime blog creating LaCroix themed R graphs using LaCroixColoR & Magick animationscontinue reading.
Facebook Twitter Google+ LinkedIn W przyszły piątek (8 czerwca) na wydziale MiNI PW odbędzie się konferencja Data Science Summit. W sali 107 pomiędzy 10:50 a 11:20 ma miejsce mój referat...continue reading.
If you build statistical or machine learning models, the recipes package can be useful for data preparation. A recipe object is a container that holds all the steps that should...continue reading.
Native scoring is a much overlooked feature in SQL Server 2017 (available only under Windows and only on-prem), that provides scoring and predicting in pre-build and stored machine learning models...continue reading.