Seuraa
Jouni Helske
Jouni Helske
Academy Research Fellow, University of Turku, Finland
Vahvistettu sähköpostiosoite verkkotunnuksessa utu.fi - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
KFAS: Exponential Family State Space Models in R
J Helske
Journal of Statistical Software 78 (10), 2017
182*2017
Introducing libeemd: a program package for performing the ensemble empirical mode decomposition
PJJ Luukko, J Helske, E Räsänen
Computational Statistics 31, 545-557, 2016
162*2016
Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R
S Helske, J Helske
Journal of Statistical Software 88 (3), 2019
1432019
Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo
M Vihola, J Helske, J Franks
Scandinavian Journal of Statistics 47, 1339– 1376, 2020
42*2020
Combining sequence analysis and hidden Markov models in the analysis of complex life sequence data
S Helske, J Helske, M Eerola
Sequence analysis and related approaches: Innovative methods and …, 2018
412018
Can visualization alleviate dichotomous thinking? Effects of visual representations on the cliff effect
J Helske, S Helske, M Cooper, A Ynnerman, L Besancon
IEEE Transactions on Visualization and Computer Graphics, 2021
352021
A Bayesian reconstruction of a historical population in Finland, 1647–1850
M Voutilainen, J Helske, H Högmander
Demography 57 (3), 1171-1192, 2020
172020
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
F Lindsten, J Helske, M Vihola
Advances in Neural Information Processing Systems 31, 2018
152018
Analysing complex life sequence data with hidden Markov modelling
S Helske, J Helske, M Eerola
International Conference on Sequence Analysis and Related Methods, 2016
132016
bssm: Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R
J Helske, M Vihola
R Journal, 2021
11*2021
A modern approach to transition analysis and process mining with Markov models in education
J Helske, S Helske, M Saqr, S López-Pernas, K Murphy
Learning Analytics Methods and Tutorials: A Practical Guide Using R, 381-427, 2024
10*2024
From sequences to variables–Rethinking the relationship between sequences and outcomes
S Helske, J Helske, GK Chihaya
Sociological Methodology, 2023
92023
Clustering and structural robustness in causal diagrams
S Tikka, J Helske, J Karvanen
Journal of Machine Learning Research 24 (195), 1-32, 2023
82023
Estimation of causal effects with small data in the presence of trapdoor variables
J Helske, S Tikka, J Karvanen
Journal of the Royal Statistical Society: Series A (Statistics in Society), 2021
82021
A nonlinear mixed model approach to predict energy expenditure from heart rate
L Kortelainen, J Helske, T Finni, L Mehtätalo, O Tikkanen, S Kärkkäinen
Physiological Measurement 42 (3), 035001, 2021
62021
seqHMM: Mixture hidden Markov models for social sequence data and other multivariate, multichannel categorical time series (1.2. 0)[Computer software]
J Helske, S Helske
62021
Estimating aggregated nutrient fluxes in four Finnish rivers via Gaussian state space models
J Helske, J Nyblom, P Ekholm, K Meissner
Environmetrics 24 (4), 237-247, 2013
62013
Estimating the causal effect of timing on the reach of social media posts
L Valkonen, J Helske, J Karvanen
Statistical Methods & Applications 32 (2), 493-507, 2023
42023
dynamite: An R Package for Dynamic Multivariate Panel Models
S Tikka, J Helske
arXiv preprint arXiv:2302.01607, 2023
32023
diagis: Diagnostic plot and multivariate summary statistics of weighted samples from importance sampling
J Helske
32016
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Artikkelit 1–20