Juha Karvanen
@juhakarvanen.bsky.social
170 followers 290 following 7 posts
Professor of Statistics at University of Jyväskylä. Interested in causal models, study design, and missing data. Homepage: http://users.jyu.fi/~jutakarv/
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juhakarvanen.bsky.social
In a new preprint, we study causal effect identification with multiple data sources. We show that certain clustering and pruning operations of the causal graph are identification invariant. This means that we may use the smaller graph to make conclusions on the larger graph.
arxiv.org/abs/2505.15215
Clustering and Pruning in Causal Data Fusion
Data fusion, the process of combining observational and experimental data, can enable the identification of causal effects that would otherwise remain non-identifiable. Although identification algorit...
arxiv.org
juhakarvanen.bsky.social
Our paper on the value of information for a risk-averse decision maker was published. Koski, V., Karvanen, J. Risk aversion in the value of information analysis: application to lake management. Stochastic Environmental Research and Risk Assessment (2025) doi.org/10.1007/s004...
Figure on the value of information as a function of different parameters
Reposted by Juha Karvanen
ellisinstitute.fi
ELLIS Institute Finland is hiring Principal Investigators in AI + machine learning. World-class resources for research incl. LUMI supercomputer, generous starting package & professorship affiliation with a university in the world’s happiest country! Apply by March 9: ellisinstitute.fi/PI-recruit
Logo of ELLIS Institute Finland (line drawn map of Europe)
Reposted by Juha Karvanen
riskyristo.bsky.social
The SBEDE model is released!
It is a statistical model for debiasing systematic biases in expert predictions and ignoring experts who have not proven their competence
#BayesianStats
The article includes a real data portfolio optimization application with stock analysts' target prices
rdcu.be/d3n69
A Bayesian model for portfolio decisions based on debiased and regularized expert predictions
rdcu.be
juhakarvanen.bsky.social
Scholar Goggler summarized my research topics.
scholargoggler.com
A word cloud. "Causal", "data" and "physical" have the largest font size.
juhakarvanen.bsky.social
Santtu Tikka and I wrote two preprints on identification in missing data problems. The results have interesting implications for multiple imputation.

Multiple imputation and full law identifiability, arxiv.org/abs/2410.18688

Monotone missing data: a blessing and a curse, arxiv.org/abs/2411.03848
Multiple imputation and full law identifiability
The key problems in missing data models involve the identifiability of two distributions: the target law and the full law. The target law refers to the joint distribution of the data variables, while ...
arxiv.org
juhakarvanen.bsky.social
Forestry is important for the economies of Finland and Sweden and provides interesting problems also for statisticians. In a recent work done in collaboration with Skogforsk, we optimized the inventory decisions in operational forestry. doi.org/10.1093/biom...
The optimal mix of inventory methods as a function of the inventory budget.
juhakarvanen.bsky.social
Simulating values from a known distribution is a basic task in statistics. But how to simulate from a counterfactual distribution? We consider this question in a recently published paper.

jair.org/index.php/ja...

The proposed algorithm is applied to fairness analysis in credit-scoring.
A simulation algorithm