| mvabund: Statistical methods for analysing multivariate abundance data Y Wang, U Naumann, D Eddelbuettel, J Wilshire, D Warton, J Byrnes, ... R package version 4 (3), 2020 | 313 | 2020 |
| gllvm: Fast analysis of multivariate abundance data with generalized linear latent variable models in r J Niku, FKC Hui, S Taskinen, DI Warton Methods in Ecology and Evolution 10 (12), 2173-2182, 2019 | 153 | 2019 |
| Generalized linear latent variable models for multivariate count and biomass data in ecology J Niku, DI Warton, FKC Hui, S Taskinen Journal of Agricultural, Biological and Environmental Statistics 22, 498-522, 2017 | 88 | 2017 |
| Efficient estimation of generalized linear latent variable models J Niku, W Brooks, R Herliansyah, FKC Hui, S Taskinen, DI Warton PloS one 14 (5), e0216129, 2019 | 66 | 2019 |
| gllvm: Generalized linear latent variable models J Niku, W Brooks, R Herliansyah, FKC Hui, S Taskinen, DI Warton, ... R package version 1 (3), 2020 | 28 | 2020 |
| Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models J Niku, FKC Hui, S Taskinen, DI Warton Environmetrics 32 (6), e2683, 2021 | 17 | 2021 |
| Mvabund: statistical methods for analysing multivariate abundance data. Version 4.1. 6 Y Wang, U Naumann, D Eddelbuettel, J Wilshire, D Warton, J Byrnes, ... | 11 | 2020 |
| gllvm: generalized linear latent variable models. R package version 1.1. 7; 2019 J Niku, W Brooks, R Herliansyah, FKC Hui, S Taskinen, DI Warton | 8 | 2023 |
| Fast and universal estimation of latent variable models using extended variational approximations P Korhonen, FKC Hui, J Niku, S Taskinen Statistics and Computing 33 (1), 26, 2023 | 6 | 2023 |
| Package ‘gllvm.’ J Niku, W Brooks, R Herliansyah, FKC Hui, S Taskinen, DI Warton, ... R Project 326, 2017 | 6 | 2017 |
| A large-scale and long-term experiment to identify effectiveness of ecosystem restoration M Elo, S Kareksela, O Ovaskainen, N Abrego, J Niku, S Taskinen, ... bioRxiv, 2024.04. 02.587693, 2024 | 3 | 2024 |
| “gllvm: Generalized Linear Latent Variable Models.” R package version 1.2. 3 J Niku, W Brooks, R Herliansyah, FKC Hui, S Taskinen, DI Warton, ... | 3 | 2020 |
| Testate amoebae community analysis as a tool to assess biological impacts of peatland use E Daza Secco, J Haimi, H Högmander, S Taskinen, J Niku, K Meissner Wetlands Ecology and Management 26, 597-611, 2018 | 3 | 2018 |
| A comparison of joint species distribution models for percent cover data P Korhonen, FKC Hui, J Niku, S Taskinen, B van der Veen Methods in Ecology and Evolution, 2024 | 2 | 2024 |
| On modeling multivariate abundance data with generalized linear latent variable models J Niku JYU dissertations, 2020 | 1 | 2020 |
| Fungal communities associated with arcto-alpine plants are strongly shaped by regional effects M Kumar, J Niku, L Antonielli, G Brader, A Sessitsch, S Taskinen, J Dirk, ... Kumar MGK. Biogeographical diversity of plantassociated microbes in arcto …, 2016 | 1 | 2016 |
| Latenttiin muuttujamalliin perustuva ordinaatiomenetelmä J Niku | 1 | 2015 |
| Samat tavat, erilaiset tarinat–Suomalaisten pelaajien urheilupolut Jalkapallon A-maajoukkueeseen–Similar Practices, Different Stories–Finnish Players' Sporting Paths to the … M Szerovay, A Hölttä, M Paananen, H Louste, S Koski, J Rantala, J Niku JYU Reports, 2024 | | 2024 |
| Biplots Based on Latent Variable Models in the Analysis of Ecological Communities J Niku, S Taskinen Book of Abstracts, 174, 0 | | |
| Generalized Linear Latent Variable Models for Multivariate Count J Niku, DI Warton, FKC Hui, S Taskinen | | |
