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Emi Tanaka

@emitanaka.org
2.8K followers 262 following 253 posts

Statistical Data Artist & Scientist at Australian National University 🇳🇿 Interested in mixed models, experimental design, plant breeding 🌱, bioinfo 🧬, data vis 📊, statistical practice, ML/AI 👩🏻‍💻 Dabbles in UI, UX, front-end & #rstats 📦 dev emitanaka.org

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Emi Tanaka @emitanaka.org · 5h
日本語凄い!😮
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Emi Tanaka @emitanaka.org · 02/10/2026
Yeah if the student copy and paste, I figured they would see it (assuming they read what they paste). I make the instructions available on Canvas so students would copy and paste. Maybe I should make it a pdf instruction like you
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Emi Tanaka @emitanaka.org · 01/10/2026
Is your AI prompt visible to humans? Or you hid it so AI would catch it if student uploaded the whole assignment?
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Emi Tanaka @emitanaka.org · 30/09/2026
Compare efficiency across groups with different production constraints. metafrontier by Erik Enstad unifies stochastic-frontier and data-envelopment approaches, with productivity analysis and inference. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: metafrontier: Unified Metafrontier Analysis for Efficiency and Productivity in R
Comparing the technical efficiency of groups of firms that face different restrictions of a common production technology requires a metafrontier framework that envelops the group-specific frontiers. E...
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Emi Tanaka @emitanaka.org · 30/09/2026
Feature importance with uncertainty: xplainfi brings global importance methods and statistical inference to mlr3. By Lukas Burk, @fionaewald.bsky.social , @giuseppe88.bsky.social , Marvin N. Wright & Bernd Bischl, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: xplainfi: Feature Importance and Statistical Inference for Machine Learning in R
We introduce xplainfi, an R package built on top of the mlr3 ecosystem for global, loss-based feature importance methods for machine learning models. Various feature importance methods exist in R, but...
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Emi Tanaka @emitanaka.org · 30/09/2026
Model and forecast mortality in a unified R workflow. demofit by Jackie Li combines parametric mortality laws with stochastic forecasting models, helping produce smooth age profiles. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: demofit: A Unified Framework for Mortality Modelling Integrating Parametric Laws and Stochastic Models
Mortality modelling and forecasting are widely used in actuarial science and demography, with numerous parametric mortality laws and stochastic mortality models proposed to describe age-specific patte...
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Emi Tanaka @emitanaka.org · 30/09/2026
Denoise images while preserving edges! DRIP by Yicheng Kang brings jump regression to R, with methods for detecting discontinuities, reconstructing surfaces and deblurring images. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: DRIP: An R Package for Jump Regression and Image Analysis
Jump regression performs nonparametric regression analysis where the regression function can be discontinuous. Because of its ability to conduct jump detection and jump-preserving estimation, jump reg...
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Emi Tanaka @emitanaka.org · 30/09/2026
Do two gene lists convey equivalent biological information? goSorensen combines Gene Ontology enrichment, equivalence testing and visualisation. By Pablo Flores and colleagues, in The R Journal. #Bioconductor #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
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Emi Tanaka @emitanaka.org · 30/09/2026
Put time series on the map! sugarglider adds ribbon and segment glyphs to reveal seasonal patterns and data ranges across locations. By Maliny Po, S. Nathan Yang, H. @huizezhangsherry.bsky.social & @visnut.bsky.social , in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
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Emi Tanaka @emitanaka.org · 30/09/2026
How sensitive are causal conclusions to selection bias? SelectionBias by Stina Zetterstrom & Ingeborg Waernbaum computes bounds for causal risk ratios and risk differences. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: SelectionBias: An R Package for Bounding Selection Bias in Causal Estimands
Selection bias may arise when there are dropouts or missing data in the analysis, or when subjects are included or excluded in the analysis based upon some selection criteria for the study populatio...
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Emi Tanaka @emitanaka.org · 30/09/2026
Sparse Bayesian neural networks in R: LBBNN combines uncertainty quantification, explanations and GPU-capable variational inference via torch. By Lars Skaaret-Lund, Eirik Høyheim & Aliaksandr Hubin, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: LBBNN: An R Package for Sparse and Explainable Bayesian Deep Learning with Latent Binary Bayesian Neural Networks
The package LBBNN (latent binary Bayesian neural networks) provides a framework for doing sparse uncertainty aware and to a large degree interpretable Bayesian inference in neural network models, with...
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Emi Tanaka @emitanaka.org · 30/09/2026
What if a spatial point's marks depend on its location? ldmppr by Lane Drew & Andee Kaplan provides estimation, simulation, evaluation and visualisation for location-dependent marked point processes. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: ldmppr: Location Dependent Marked Point Processes in R
In this article, we present ldmppr, an R package for estimating, evaluating, simulating from, and visualizing location-dependent marked spatial point processes. To date, it has commonly been assumed t...
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Emi Tanaka @emitanaka.org · 30/09/2026
Numeric, binary and categorical variables in one dataset? dbrobust offers robust distance measures and visualisations for mixed-type data. By Eva Boj, Aurea Grané & Marcos Álvarez, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: R Package dbrobust: Robust Distance-Based Visualization and Analysis of Mixed-Type Data
In many applied fields, such as socioeconomic research, quality of life analysis or gender inequality studies, datasets often contain a mixture of quantitative, binary and categorical variables. Tradi...
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Emi Tanaka @emitanaka.org · 30/09/2026
Comparing rankings against a reference? rSRD simplifies Sum of Ranking Differences analysis, including permutation tests, cross-validation and plotting. By Balázs R. Sziklai and colleagues, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: rSRD: An R Package for the Sum of Ranking Differences Statistical Procedure
Sum of Ranking Differences (SRD) is a relatively novel, non-parametric statistical procedure that has become increasingly popular recently. SRD compares solutions via a reference by applying a rank tr...
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Emi Tanaka @emitanaka.org · 30/09/2026
How many regimes does your time series need? MSTest by Gabriel Rodriguez-Rondon & Jean-Marie Dufour provides tests for Markov switching models, alongside estimation and simulation tools. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: MSTest: An R Package for Testing Markov Switching Models
We present the R package MSTest, which implements hypothesis testing procedures to determine the number of regimes in Markov switching models. These models have wide-ranging applications in economics,...
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Emi Tanaka @emitanaka.org · 30/09/2026
Explore nonlinear multivariate time series with mtarm: Bayesian threshold autoregressive modelling, forecasting and model assessment in R. By Luis Hernando Vanegas and colleagues, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: mtarm: Bayesian Analysis of Multivariate Threshold Autoregressive Models in R
This paper introduces mtarm, an R package for Bayesian estimation, inference, and forecasting in multivariate Threshold Autoregressive (TAR) models. The package supports both standard m-step-ahead for...
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Emi Tanaka @emitanaka.org · 30/09/2026
Many time series, many parameters: VARshrink by Namgil Lee & Sung-Ho Kim brings shrinkage estimation to high-dimensional vector autoregressive models in R. Read their workflow in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: VARshrink: An R Package for Shrinkage Estimation of High-Dimensional Vector Autoregressive Models
Vector autoregressive (VAR) models are widely used to study dynamic relationships in multivariate time series, with applications ranging from economic and financial forecasting to gene network analysi...
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Emi Tanaka @emitanaka.org · 30/09/2026
New in The R Journal: ODRF by Yu Liu & Yingcun Xia implements oblique decision trees and random forests, using combinations of predictors for splits. Includes boosting, visualisation and online tree updates. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: ODRF: An R Package for Oblique Decision Tree and Its Random Forest
The classification and regression tree (CART) and Random Forest (RF) are popular machine learning methods that involve selecting one predictor at a time as the splitting variable for each node. The us...
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Emi Tanaka @emitanaka.org · 30/09/2026
Automatic forecasting with echo state networks: echos by Alexander Häußer offers lightweight modelling with both base R and tsibble/fable interfaces. Explore reproducible examples in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: echos: An R Package for Automatic Time Series Forecasting using Echo State Networks
The paper introduces echos, an R package for automatic univariate time series modeling and forecasting using Echo State Networks (ESNs). ESNs represent an efficient and flexible method that combines r...
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Emi Tanaka @emitanaka.org · 30/09/2026
A known distribution mixed with an unknown component? admix supports estimation, testing and clustering for these contamination models. By Xavier Milhaud and colleagues, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: Admix: An R Package for Estimation, Test and Clustering in Admixture Models
The R package admix, available on CRAN, implements a wide variety of functions dedicated to estimation, tests and clustering of admixture models, also known as contamination models. Such models are tw...
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Emi Tanaka @emitanaka.org · 30/09/2026
Simulating high-dimensional truncated normal distributions? hdtg provides scalable samplers in R. New in The R Journal, by Zhenyu Zhang, Andrew Chin, Akihiko Nishimura & @msuchard.bsky.social. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: hdtg: An R Package for High-Dimensional Truncated Normal Simulation
Simulating from the multivariate truncated normal distribution (MTN) is required in various statistical applications yet remains challenging in high dimensions. Currently available algorithms and thei...
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Emi Tanaka @emitanaka.org · 30/09/2026
Reduce predictors while retaining information for regression or classification. psvmSDR by Jungmin Shin, Seung Jun Shin & Andreas Artemiou unifies principal-machine methods for dimension reduction. New in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: psvmSDR: An R Package for a Unified Algorithm for Sufficient Dimension Reduction via Principal Machines
Sufficient dimension reduction (SDR), which seeks a lower-dimensional subspace of the predictors containing regression or classification information, has been popular in a machine learning community. ...
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Emi Tanaka @emitanaka.org · 30/09/2026
Uneven time gaps? iAR offers autoregressive models designed for irregularly observed time series, with tools for estimation, simulation, forecasting and interpolation. By Felipe Elorrieta and colleagues, in The R Journal. #rstats journal.r-project.org/articles/RJ-...
journal.r-project.org
The R Journal: iAR: An R Package for Autoregressive Modeling Irregularly Observed Time Series
iAR is an R package that provides tools for handling autoregressive models irregularly observed, for one or two dimensions, stationary time series. The standard autoregressive (AR) model is not suitab...
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Emi Tanaka @emitanaka.org · 30/09/2026
Please note that the following summaries are AI-generated. Apologies for any mistakes.
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Emi Tanaka @emitanaka.org · 30/09/2026
I’m pleased to announce that Vol 18 Issue 3 of The R Journal is out now! 🥳 Free & open access, R journal is made possible by our volunteer editors, reviewers + contributing authors. Thank you all! journal.r-project.org/issues/2026-3/ 🧵 20 articles 👇 #rstats journal.r-project.org/issues/2026-3/
journal.r-project.org
The R Journal: Volume 18/3
Articles published in the September 2026 issue
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Reposted by Emi Tanaka
R Consortium @rconsortium.bsky.social · 21/09/2026
What does it take to sustain R? Join R Consortium, R Core & R Foundation Oct 6 to discuss the people, infrastructure & community behind R. 12 PM PT / 3 PM ET / 8 PM London Register: r-consortium.org/webinars/sus... #RStats
Graphic for upcoming R Core and R Foundation panel discussion - Oct 6, 2026
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Emi Tanaka @emitanaka.org · 22/09/2026
+1 to Susan. Also @nrennie.bsky.social @visnut.bsky.social if not on the list already
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Emi Tanaka @emitanaka.org · 16/09/2026
Love the drawings!
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Reposted by Emi Tanaka
Dariia Mykhailyshyna @dariia.bsky.social · 08/09/2026
This workshop is in two days so don’t forget to register ! Details: bit.ly/3wBeY4S Please share! #AcademicSky #EconSky #RStats
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Emi Tanaka @emitanaka.org · 06/09/2026
Congratulations! Your modelsummary package is great too!
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Emi Tanaka @emitanaka.org · 21/08/2026
Making good use of my annual leave 🤗 🍚
Atsuko on the big screenAtsuko on the side walk screen
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Emi Tanaka @emitanaka.org · 12/08/2026
All hail our new President 🎉🎉🎉
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Emi Tanaka @emitanaka.org · 09/08/2026
More continuing positions at the Australian National University! 🇦🇺🦘🐨 ⭐ Biostatistician - apply by 4 Sep 2026 23:55 AEST: jobs.anu.edu.au/jobs/researc... ⭐ Senior Data Scientist - apply by 23 Aug 2026 23:55 AEST: jobs.anu.edu.au/jobs/senior-... #Statistics #StatsJobs
jobs.anu.edu.au
Research Fellow (Biostatistician) - Canberra / ACT, ACT, Australia
Classification: Academic Level BSalary package: $124,638 - $141,317 per annum plus 17% superannuation Terms: Full time, Continuing Opportunity to undertake high-quality independent research in Biosta...
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Reposted by Emi Tanaka
Martyn Plummer @martynplummer.bsky.social · 07/08/2026
Come and work with us! If you have a PhD in Statistics (or related subject) and are looking to develop a teaching focused career in academia then please get in touch. We have a very strong teaching team here.
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Emi Tanaka @emitanaka.org · 06/08/2026
📢🇦🇺 Australian National University is recruiting a continuing Senior Data Scientist 👩‍💻🧑‍💻 Bring your statistical expertise and help turn data into meaningful university-wide insights 📊 📅 Apply by 23 Aug 2026 23:55 AEST #Statistics #StatsJobs jobs.anu.edu.au/jobs/senior-...
jobs.anu.edu.au
Senior Data Scientist - Canberra / ACT, ACT, Australia
Classification: ANU Senior Manager 1 (Administration)Salary package: $141,637 - $148,403 per annum plus 17% superannuationTerms: Full-time, Continuing The Position Operating under broad strategic guid...
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Emi Tanaka @emitanaka.org · 24/07/2026
I default count on extensions 😅
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Reposted by Emi Tanaka
Ben Harrap @bharrap.bsky.social · 24/07/2026
You thought abstract submissions for the Australian Data Science Network Conference were closing today? Nope! Like all good conferences, we're extending the deadline by one week. The final deadline is July 31st (for real this time!) adsnconf2026.netlify.app @ardc.edu.au #statssky #datascience
adsnconf2026.netlify.app
Australian Data Science Network Conference 2026 – ADSN2026
26th & 27th November 2026, Australian Bureau of Statistics House, Canberra
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Emi Tanaka @emitanaka.org · 22/07/2026
The coveted honorary position!
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Emi Tanaka @emitanaka.org · 22/07/2026
I never realised eduroam can be found outside of uni. Well now Brisbane airport is the best airport in Australia in my view
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Emi Tanaka @emitanaka.org · 22/07/2026
There's eduroam at Brisbane airport!! And it works! What?! How good is that!
Wifi
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Emi Tanaka @emitanaka.org · 22/07/2026
Great minds indeed! 😂
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Emi Tanaka @emitanaka.org · 21/07/2026
Ah cool! I've done the same before for base R vs tidyverse: emitanaka.org/rsyntax/data...
emitanaka.org
Base R and Tidyverse syntax comparison for data wrangling – R Syntax
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Reposted by Emi Tanaka
Dr Liz Allen @drdemography.com · 21/07/2026
ANU has been to hell and back. It’s time we come together. It’s time for a BIG community block party! ANU turns 80 this year and to celebrate the campus is opening up to all. Please come along. Bring your friends, the family! There’s free face painting!! www.anu.edu.au/about/our-hi...

ANU Community Day on 15
August
The Australian National University (ANU) turns 80 this year, and we're inviting Canberra to join the celebration. Experience our beautiful campus and discover the rich stories of the ANU community.
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Emi Tanaka @emitanaka.org · 16/07/2026
Got to hang with the cool ladies 🪭
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Reposted by Emi Tanaka
Karen Lamb @kelamb.bsky.social · 16/07/2026
Fantastic talk from @emitanaka.org on working with LLMs in #datascience at #ICOTS12. Highlights thinking of interacting with AI as a junior analyst with the statistician/data scientist in a manager/supervisor role to review/quality control output. Always enjoy hearing Emi talk! #statistics #teaching
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Emi Tanaka @emitanaka.org · 14/07/2026
Education can benefit from being open like software I reckon
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Emi Tanaka @emitanaka.org · 11/07/2026
I didn't realise you were there!
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Emi Tanaka @emitanaka.org · 11/07/2026
@nicolewhite.bsky.social and @kelamb.bsky.social and co did a great job running this event. Superbly organised and really impressed how the two hub event run so smoothly. Thank you for organising the event! 👏👏👏
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Emi Tanaka @emitanaka.org · 11/07/2026
Get in touch with @myramcguinness.bsky.social if you're looking for an enthusiastic and experienced biostatistician 👇
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Emi Tanaka @emitanaka.org · 09/07/2026
Here?
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