Hi, I am Artur 👋

I'm an economist, researcher and teacher who loves to play around with data 📈. I am also passionate about contributing 💻 open-source packages for my favourite open-source software package named 🌟Gretl🌟 (http://gretl.sourceforge.net/).

Open-source projects 🔭

Sublime editor extension for Gretl and Hansl

In case you use gretl and the Sublime editor, here is my official Hansl-Gretl-Language package:

https://packagecontrol.io/packages/Hansl-Gretl-Language

Gretl cheat-sheet

I've written a Gretl cheat-sheet on basic data handling, plotting etc. which is available here.

Gretl tutorial

Here you find tutorial(s) on how to use Gretl.

Gretl packages I've co-authored

I am (co-)author of various official user-contributed packages for gretl. Here a list:

• ADMBP: ARDL Dynamic Multiplier Bootstrap Package (https://github.com/atecon/ADMPB)
• assertion: Assert functions for verifying expectations and values in gretl tests (https://github.com/atecon/assertion)
• auto_arima: Return best ARIMA model according to information criteria value (https://github.com/atecon/auto_arima)
• BMST: Logit and Probit model specifcation tests package (https://github.com/atecon/bmst)
• calendar_utils: Collection of useful date time related tools (https://github.com/atecon/calendar_utils)
• candlesticks: Create candlesticks chart for financial data (https://github.com/atecon/candlesticks)
• CategoryEncoders: Encoder based on categorical variables (https://github.com/atecon/CategoryEncoders)
• cointARDL: Bootstrap single-equation cointegration tests (https://github.com/atecon/cointARDL)
• CvDataSplitter: Compile cross-validation datasets (https://github.com/atecon/cv_data_splitter)
• distances: Compute pairwise metrics and affinities using gretl. (https://github.com/atecon/distances)
• fsboost: Create factorized kernel-density plots (https://github.com/atecon/fdensity/)
• fsboost: Implementation of the forward-stagewise shrinkage & selection estimator (https://github.com/atecon/fsboost/)
• gregory_hansen: Residual-based tests for cointegration in models with regime shifts (https://github.com/atecon/gregory_hansen)
• holidays: Retrieve list of holiday series (https://github.com/atecon/holidays)
• knn: KNN supervised learning algorithm for regression and classification (https://github.com/atecon/knn)
• kmeans: K-means unsupervised learning algorithm (https://github.com/atecon/kmeans)
• latextab: Write matrix as Latex table (https://github.com/atecon/latextab)
• logging: Record the history and progress of a computation as a log of events (https://github.com/atecon/logging)
• mat2data: Write matrix as dataset to some file (e.g. csv, gdt) (https://github.com/atecon/mat2data)
• memusage: Compute memory usage of gretl objects (https://github.com/atecon/memusage)
• metadata: Package for retrieving metadata from gdt-files (https://github.com/atecon/metadata)
• multiplot: Combine multiple plots to a single graph (https://github.com/atecon/multiplot)
• naiveFC: Simple forecasting methods (https://github.com/atecon/naivefc)
• PandasPort: Collection of tools for handling datasets (https://github.com/atecon/PandasPort)
• PanelTools: Collection of tools for handling panel data (https://github.com/atecon/PanelTools)
• PairPlot: Scatterplot matrix with factor separation (https://github.com/atecon/pairplot)
• pcaTools: Conduct (sparse) PCA analysis; scree-plot and bi-plot support (https://github.com/atecon/pcaTools)
• pkgchecker: Fin unused variables and functions, and compile a 1-level dependency graph (https://github.com/atecon/pkgchecker)
• pmbb: Moving Blocks Bootstrap (MBB) for linear panels (https://github.com/atecon/pmbb)
• ridge: Ridge regression (https://github.com/atecon/ridge) archive
• RollingStats: Rolling Time-Series Statistics (https://github.com/atecon/Rolling_Stats)
• SB: Stationary bootstrap resampling of time series (http://ricardo.ecn.wfu.edu/gretl/cgi-bin/current_fnfiles/SB.gfn)
• season_plot: Plot seasonal time-series components (https://github.com/atecon/season_plot)
• stack_data: Stack list of series (https://github.com/atecon/stack)
• string_utils: Helper functions for string operations (https://github.com/atecon/string_utils)
• StrucTiSM: Estimating and forecasting using structural time-series models (https://github.com/atecon/StrucTiSM)
• Threshold_Panel: Panel threshold model (Bruce Hansen, JoE 1999) (https://github.com/atecon/Threshold_Panel)
• VARrec: Recursive computation of VAR model coefficient estimates (https://github.com/atecon/VARrec)
• var_chow: Chow test for VAR models (bootstrap version) (https://github.com/atecon/var_chow)
• FEP: Forecast Evaluation Package (https://github.com/atecon/fep)

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