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Mathematics

D-Index
34
Citations
4388
World Ranking
2932
National Ranking
22

Overview

Elja Arjas is affiliated with the University of Helsinki in Finland and specializes in mathematical and statistical research, with a particular focus on statistics and probability. Their academic output includes work in management science and operations research, pathology and forensic medicine, molecular biology, and cancer research.

The scientist's main fields of study are:

  • Mathematics

Within this domain, the subfields they have contributed to include:

  • Statistics and Probability
  • Management Science and Operations Research
  • Pathology and Forensic Medicine
  • Molecular Biology
  • Cancer Research

Elja Arjas has addressed a variety of research topics over their career. The principal areas of focus include:

  • Statistical Methods in Clinical Trials
  • Advanced Causal Inference Techniques
  • Statistical Methods and Inference
  • Optimal Experimental Design Methods
  • Genetic factors in colorectal cancer
  • Gene expression and cancer classification
  • Cancer Genomics and Diagnostics

The scientist has published in several academic venues, notably:

  • arXiv (Cornell University)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • Molecular Oncology
  • Bayesian Analysis
  • BMC Medical Research Methodology

Recent publications authored or co-authored by Elja Arjas comprise:

  • A discrete time method for the analysis of event histories (2021, OPAL (Open@LaTrobe) (La Trobe University))
  • Transcriptomic pan-cancer analysis using rank-based Bayesian inference (2022, Molecular Oncology)
  • Bayesian Non-Parametric Ordinal Regression Under a Monotonicity Constraint (2022, Bayesian Analysis)
  • Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective (2022, BMC Medical Research Methodology)
  • Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective (2021, Research Square (Research Square))

Their collaborative work includes partnerships with several frequently co-authoring researchers, namely:

  • Dario Gasbarra
  • Pekka Kangas
  • Valeria Vitelli
  • Thomas Fleischer
  • Jørgen Ankill

Best Publications

  • Bayesian spatial modeling of genetic population structure

    Jukka Corander;Jukka Sirén;Elja Arjas

  • Bayesian Mapping of Multiple Quantitative Trait Loci From Incomplete Inbred Line Cross Data

    Mikko J. Sillanpää;Elja Arjas

  • A Graphical Method for Assessing Goodness of Fit in Cox's Proportional Hazards Model

    Elja Arjas

  • Bayesian mapping of multiple quantitative trait loci from incomplete outbred offspring data.

    Mikko J. Sillanpää;Elja Arjas

  • The Claims Reserving Problem in Non-Life Insurance: Some Structural Ideas

    Elja Arjas

  • Bayesian methods for analyzing movements in heterogeneous landscapes from mark-recapture data.

    Otso Ovaskainen;Hanna Rekola;Evgeniy Meyke;Elja Arjas

  • Non-parametric Bayesian Estimation of a Spatial Poisson Intensity

    Juha Heikkinen;Elja Arjas

  • Survival models and martingale dynamics: original text, discussion and reply

    Elja Arjas;N. Keiding;O. Borgan;P. K. Andersen

  • Transmission of pneumococcal carriage in families: a latent Markov process model for binary longitudinal data

    Kari Auranen;Elja Arjas;Tuija Leino;Aino K. Takala

  • Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

    Päivi Hurme;Mikko J. Sillanpää;Elja Arjas;Tapani Repo

  • The Failure and Hazard Processes in Multivariate Reliability Systems

    Elja Arjas

  • Causal Reasoning from Longitudinal Data

    Elja Arjas;Jan Parner

  • BAYESIAN ANALYSIS OF METAPOPULATION DATA

    R. B. O'Hara;E. Arjas;H. Toivonen;I. Hanski

  • Discussion on the paper by Spiegelhalter, Sherlaw-Johnson, Bardsley, Blunt, Wood and Grigg

    Deborah Ashby;Sheila M. Bird;Ian Hunt;Robert Grant

  • A Stochastic Process Approach to Multivariate Reliability Systems: Notions Based on Conditional Stochastic Order

    Elja Arjas

  • Poliovirus Surveillance by Examining Sewage Water Specimens: Studies on Detection Probability Using Simulation Models

    J. Ranta;T. Hovi;E. Arjas

  • CLAIMS RESERVING IN CONTINUOUS TIME; A NONPARAMETRIC BAYESIAN APPROACH

    Svend Haastrup;Elja Arjas

  • Probabilistic preference learning with the Mallows rank model

    Valeria Vitelli;Øystein Sørensen;Marta Crispino;Arnoldo Frigessi

  • A Marked Point Process Approach to Censored Failure Data with Complicated Covariates

    Elja Arjas;Pentti Haara

  • On predictive causality in longitudinal studies

    Elja Arjas;Mervi Eerola

  • A Note on Random Intensities and Conditional Survival Functions

    Anatoli Yashin;Elja Arjas

  • Approximating Many Server Queues by Means of Single Server Queues

    Elja Arjas;Tapani Lehtonen

  • Approximating many-server queues by means of single-server queues

    Elja Arjas;Tapani Lehtonen

  • Bayesian integrated modeling of expression data: a case study on RhoG

    Rashi Gupta;Dario Greco;Petri Auvinen;Elja Arjas;Elja Arjas

Frequent Co-Authors

Terence P. Speed
Terence P. Speed Walter and Eliza Hall Institute of Medical Research
Petri Auvinen
Petri Auvinen University of Helsinki
Tommi Härkänen
Tommi Härkänen Finnish Institute for Health and Welfare (THL)
Richard L. Tweedie
Richard L. Tweedie University of Minnesota
Jukka Corander
Jukka Corander University of Oslo
Jaakko Tuomilehto
Jaakko Tuomilehto University of Helsinki
Matti Pirinen
Matti Pirinen University of Helsinki
Alfred Stein
Alfred Stein University of Twente
P. Helena Mäkelä
P. Helena Mäkelä University of Helsinki
Stephen E. Fienberg
Stephen E. Fienberg Carnegie Mellon University

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